CS4132 Data Analytics
Games as an entertainment intustry has blown up in the past few decades, with it overtaking Hollywood as the highest grossing entertainment industry. Gaming has also been substantially driven by ratings and sales for each games. These can be due to or affected also by the date they are released, its genre, and also how much searches a certain game may have had. As a result, I will like to look at games from metacritic, see how they have done over multiple genres, platforms, years and also analyse the amount of searches they had in different countries.
Question 1: What are the genres with the most games released? What are the genres which have the most interest about in Google? Is there any correleation between both types of genres?
Question 2: Do certain platforms more games? Do their median rating also vary over years and genres?
Question 3: When do companies release their games? Does the date of release affect its sales?
Question 4: How is the rating distributed? How has it changed over years and over different genres?
Question 5: What are the most searched genres over the years? What are the most searched genres and games over different regions over the years?
https://www.metacritic.com/browse/games/score/metascore/year/all/filtered?year_selected=2022&view=detailed&sort=desc&page=0 This data contains the top rated PC games for every year. From all of the games, we will scrape the name, platform and year, and also the link to the review of the game. We will scrape all of the pages for all the years up to 2000.
1.1 https://www.metacritic.com/game/xbox-series-x/elden-ring
This is the link for each game. From it we scrape the day, month and genres of the game. Finally we also scrape the metascore of the game
https://trends.google.com/trends/explore?q=%2Fm%2F03lm3
This data is used to see the popularity of the games worldwide. We will retrive both the interest over time and interest by region portions
2.1 https://pypi.org/project/pytrends/ The python library that helps me request Google Trends for data
https://www.vgchartz.com/games/games.php?page=1&results=200&order=Sales&ownership=Both&direction=DESC&showtotalsales=1&shownasales=0&showpalsales=0&showjapansales=0&showothersales=0&showpublisher=0&showdeveloper=0&showreleasedate=0&showlastupdate=0&showvgchartzscore=0&showcriticscore=0&showuserscore=0&showshipped=1
This data shows the game sales for most of the games. From this webpage, the Total Shipped and Total Sales will be scraped. From this, whichever is not null will be used as the sales of a game. I am scraping all the pages until the sales are 0.00 m as they are mostly outliers due to being poorly made cheap games, or they have no data at all.
import pandas as pd
from tqdm.auto import tqdm
import matplotlib.pyplot as plt
import seaborn as sns
import plotly.express as px
import plotly.graph_objects as go
from scipy import signal
from plotly.subplots import make_subplots
import geopandas as gpd
from geopandas import GeoDataFrame
from IPython.display import display
The code for the webscraping of the data will be in the Appendix.
pd.read_csv('metaScrape.csv', index_col=0)
| name | data | year | month | link | |
|---|---|---|---|---|---|
| 0 | Elden Ring | Xbox Series X | 2022 | NaN | https://www.metacritic.com//game/xbox-series-x... |
| 1 | Elden Ring | PlayStation 5 | 2022 | NaN | https://www.metacritic.com//game/playstation-5... |
| 2 | Portal Companion Collection | Switch | 2022 | NaN | https://www.metacritic.com//game/switch/portal... |
| 3 | Elden Ring | PC | 2022 | NaN | https://www.metacritic.com//game/pc/elden-ring |
| 4 | The Stanley Parable: Ultra Deluxe | Xbox Series X | 2022 | NaN | https://www.metacritic.com//game/xbox-series-x... |
| ... | ... | ... | ... | ... | ... |
| 19480 | Resident Evil: Survivor | PlayStation | 2000 | NaN | https://www.metacritic.com//game/playstation/r... |
| 19481 | ECW Anarchy Rulz | Dreamcast | 2000 | NaN | https://www.metacritic.com//game/dreamcast/ecw... |
| 19482 | Duke Nukem: Land of the Babes | PlayStation | 2000 | NaN | https://www.metacritic.com//game/playstation/d... |
| 19483 | Mortal Kombat: Special Forces | PlayStation | 2000 | NaN | https://www.metacritic.com//game/playstation/m... |
| 19484 | HBO Boxing | PlayStation | 2000 | NaN | https://www.metacritic.com//game/playstation/h... |
19485 rows × 5 columns
This dataframe is the original scraping of all the games in metacritic. name column contains the name of the game; data column contains the platform the game was released; year column contains the year it was released; month column is NaN, as it will be collected later in another scraping, which is using the links in the link column which has the metacratic link of each game. This dataframe will be mainly used due to the data column, as it is the only dataframe where duplicate names are not removed, thus causing there to be one platform for each game
pd.read_csv('metaScrape3.csv', index_col=0)
| name | data | year | month | link | index | genre | day | rating | Code | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Elden Ring | Xbox Series X | 2022 | Feb | https://www.metacritic.com//game/xbox-series-x... | 0 | Role-Playing,Action RPG | 25 | 96 | /g/11h3z4_20j |
| 2 | The Stanley Parable: Ultra Deluxe | Xbox Series X | 2022 | Apr | https://www.metacritic.com//game/xbox-series-x... | 2 | Adventure,3D,First-Person | 27 | 93 | /g/11j53dfzz5 |
| 3 | God of War (2018) | PC | 2022 | Jan | https://www.metacritic.com//game/pc/god-of-war | 3 | Action Adventure,Linear | 14 | 93 | /m/02qyf34 |
| 4 | Immortality | Xbox Series X | 2022 | Aug | https://www.metacritic.com//game/xbox-series-x... | 4 | Adventure,General | 30 | 90 | Immortality |
| 5 | Cuphead in the Delicious Last Course | Xbox One | 2022 | Jun | https://www.metacritic.com//game/xbox-one/cuph... | 5 | Action,Platformer,2D | 30 | 92 | /g/11ghtdw1pq |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 12588 | MTV Sports: Skateboarding featuring Andy Macdo... | PlayStation | 2000 | Sep | https://www.metacritic.com//game/playstation/m... | 12588 | Sports,Alternative,Skateboarding | 12 | 40 | /m/0kypkkl |
| 12589 | Resident Evil: Survivor | PlayStation | 2000 | Aug | https://www.metacritic.com//game/playstation/r... | 12589 | Action Adventure,Horror | 30 | 39 | /g/11hdvdpwm3 |
| 12590 | Duke Nukem: Land of the Babes | PlayStation | 2000 | Sep | https://www.metacritic.com//game/playstation/d... | 12590 | Action,Shooter,Third-Person,Sci-Fi | 19 | 37 | /m/0977sd |
| 12591 | Mortal Kombat: Special Forces | PlayStation | 2000 | Jun | https://www.metacritic.com//game/playstation/m... | 12591 | Action,Beat-'Em-Up | 30 | 28 | Mortal Kombat: Special Forces |
| 12592 | HBO Boxing | PlayStation | 2000 | Nov | https://www.metacritic.com//game/playstation/h... | 12592 | Sports,Traditional,Boxing | 20 | 26 | /m/0kyn71x |
12058 rows × 10 columns
This dataframe is the continuation of the first one. It includes the data for all the games in metacritic. name column contains the name of the game; data column contains the platform the game was released; year column contains the year it was released; month column contains the month the game was released; link is the link to the game's metacritic page; index is just the repeated index, which was useful in the process of interacting with pytrends; genre column contains all the genres of the game; day column contains the day of the month the game was released; rating contains the metacritic score of the game which was given by critics; Code contains the google trends code of the game. If the game has no id, its name was put there. This dataframe was also used for rating, date and genre analysis.
pd.read_csv('cleaningMeta2.csv', index_col=0)
| name | data | year | month | link | index | genre | day | rating | Code | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Elden Ring | Xbox Series X | 2022 | Feb | https://www.metacritic.com//game/xbox-series-x... | 0 | Role-Playing,Action RPG | 25 | 96 | /g/11h3z4_20j |
| 2 | The Stanley Parable: Ultra Deluxe | Xbox Series X | 2022 | Apr | https://www.metacritic.com//game/xbox-series-x... | 2 | Adventure,3D,First-Person | 27 | 93 | /g/11j53dfzz5 |
| 3 | God of War (2018) | PC | 2022 | Jan | https://www.metacritic.com//game/pc/god-of-war | 3 | Action Adventure,Linear | 14 | 93 | /g/11bzs2snwf |
| 4 | Immortality | Xbox Series X | 2022 | Aug | https://www.metacritic.com//game/xbox-series-x... | 4 | Adventure,General | 30 | 90 | Immortality |
| 5 | Cuphead in the Delicious Last Course | Xbox One | 2022 | Jun | https://www.metacritic.com//game/xbox-one/cuph... | 5 | Action,Platformer,2D | 30 | 92 | /g/11ghtdw1pq |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 10807 | McFarlane's Evil Prophecy | PlayStation 2 | 2004 | Jun | https://www.metacritic.com//game/playstation-2... | 10807 | Action,General | 15 | 34 | /m/0df0bb |
| 10808 | Coliseum | PC | 2004 | Jan | https://www.metacritic.com//game/pc/coliseum | 10808 | Strategy,Breeding/Constructing,General | 6 | 32 | Coliseum |
| 10809 | Forever Worlds - Enter the Unknown | PC | 2004 | Apr | https://www.metacritic.com//game/pc/forever-wo... | 10809 | Adventure,3D,First-Person,Fantasy,Fantasy | 5 | 31 | Forever Worlds - Enter the Unknown |
| 10810 | Fear Factor: Unleashed | Game Boy Advance | 2004 | Nov | https://www.metacritic.com//game/game-boy-adva... | 10810 | Action Adventure,Modern | 17 | 30 | /m/06zpymj |
| 10811 | Ping Pals | DS | 2004 | Dec | https://www.metacritic.com//game/ds/ping-pals | 10811 | Simulation,Miscellaneous,Virtual Life,Virtual,... | 8 | 28 | /m/056bxq |
10297 rows × 10 columns
This dataframe is the continuation of the first one. It includes the data for all the games in metacritic. name column contains the name of the game; data column contains the platform the game was released; year column contains the year it was released; month column contains the month the game was released; link is the link to the game's metacritic page; index is just the repeated index, which was useful in the process of interacting with pytrends; genre column contains all the genres of the game; day column contains the day of the month the game was released; rating contains the metacritic score of the game which was given by critics; Code contains the google trends code of the game. If the game has no id, its name was put there. The code column was used to query google trends to get search data.
pd.read_csv('metaScrape4.csv', index_col=0)
| name | data | sales | |
|---|---|---|---|
| 0 | Minecraft | All | 238.00m |
| 1 | Grand Theft Auto V | All | 170.00m |
| 2 | Wii Sports | Wii | 82.90m |
| 3 | PlayerUnknown's Battlegrounds | All | 70.00m |
| 4 | Mario Kart 8 Deluxe | NS | 46.82m |
| ... | ... | ... | ... |
| 21371 | Resident Evil 5: Gold Edition | X360 | 0.00m |
| 21372 | Cradle Double Pack | DS | 0.00m |
| 21373 | Teslagrad | PSV | 0.00m |
| 21374 | Tetris: The Grand Master Ace | X360 | 0.00m |
| 21375 | Championship Bowling | XB | 0.00m |
21376 rows × 3 columns
This dataframe contains the sales data. The name column contains the name of the game; the column contains the platform the game was released on; the sales column contains the sales of the games. THis dataframe was used to make another dataframe, shown below.
pd.read_csv('sales.csv', index_col=0)
| name | data_x | year | month | link | index | genre | day | rating | Code | data_y | sales | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Elden Ring | Xbox Series X | 2022 | Feb | https://www.metacritic.com//game/xbox-series-x... | 0 | Role-Playing,Action RPG | 25 | 96 | /g/11h3z4_20j | All | 16.60 |
| 2 | God of War (2018) | PC | 2022 | Jan | https://www.metacritic.com//game/pc/god-of-war | 3 | Action Adventure,Linear | 14 | 93 | /m/02qyf34 | All | 20.47 |
| 10 | 13 Sentinels: Aegis Rim | Switch | 2022 | Apr | https://www.metacritic.com//game/switch/13-sen... | 10 | Adventure,General | 12 | 88 | /g/11bw51r_lk | PS4 | 0.50 |
| 17 | Teenage Mutant Ninja Turtles: Shredder's Revenge | Switch | 2022 | Jun | https://www.metacritic.com//game/switch/teenag... | 19 | Action,Beat-'Em-Up,2D | 16 | 87 | /g/11mx31cjc_ | All | 1.00 |
| 19 | Monster Hunter Rise | PC | 2022 | Jan | https://www.metacritic.com//game/pc/monster-hu... | 22 | Role-Playing,Action RPG | 12 | 87 | Monster Hunter Rise | All | 11.00 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 16687 | Rally Challenge 2000 | Nintendo 64 | 2000 | Jun | https://www.metacritic.com//game/nintendo-64/r... | 12585 | Driving,Racing,Rally / Offroad | 30 | 41 | /m/0fx9jm | N64 | 0.04 |
| 16691 | Resident Evil: Survivor | PlayStation | 2000 | Aug | https://www.metacritic.com//game/playstation/r... | 12589 | Action Adventure,Horror | 30 | 39 | /g/11hdvdpwm3 | PS | 0.69 |
| 16692 | Duke Nukem: Land of the Babes | PlayStation | 2000 | Sep | https://www.metacritic.com//game/playstation/d... | 12590 | Action,Shooter,Third-Person,Sci-Fi | 19 | 37 | /m/0977sd | PS | 0.07 |
| 16693 | Mortal Kombat: Special Forces | PlayStation | 2000 | Jun | https://www.metacritic.com//game/playstation/m... | 12591 | Action,Beat-'Em-Up | 30 | 28 | Mortal Kombat: Special Forces | PS | 0.20 |
| 16694 | HBO Boxing | PlayStation | 2000 | Nov | https://www.metacritic.com//game/playstation/h... | 12592 | Sports,Traditional,Boxing | 20 | 26 | /m/0kyn71x | PS | 0.21 |
5209 rows × 12 columns
This dataframe is the formed by the merging of the previous 2 dataframe. The name column contains the name of the game; data_x column contains the platform the game was released by metacritic; year column contains the year it was released; month column contains the month the game was released; link is the link to the game's metacritic page; index is just the repeated index, which was useful in the process of interacting with pytrends; genre column contains all the genres of the game; day column contains the day of the month the game was released; rating contains the metacritic score of the game which was given by critics; Code contains the google trends code of the game. If the game has no id, its name was put there. The code column was used to query google trends to get search data. The data_y columns contains the platform it was released on by VGChartz; the sales columns contains the sales of the game. This dataframe was used in the sales analysis.
pd.read_csv('genres.csv', index_col=0)
| index | genre | Code | |
|---|---|---|---|
| 0 | 0 | Role-Playing | /m/06c9r |
| 1 | 1 | Action RPG | /m/06zm8z |
| 2 | 2 | Adventure | /m/03k9fj |
| 3 | 3 | 3D | 3D |
| 4 | 4 | First-Person | /m/033th |
| ... | ... | ... | ... |
| 167 | 167 | Tank | Tank |
| 168 | 168 | Wakeboarding | Wakeboarding |
| 169 | 169 | Futuristic Sub | Futuristic Sub |
| 170 | 170 | Old Jet | /g/11c1wfk3qv |
| 170 | 171 | Street | Street |
162 rows × 3 columns
This dataframe contains genre data. It was acquired by getting the unique genres in the previous dataframe. The index column is just the repeated index, which was useful in the process of interacting with pytrends; genre column contains the unique genres; Code contains the google trends code of the genre. If the genre has no id, its name was put there. The code column was used to query google trends to get search data. It also was cleaned, as a result, it was used to remove duplicate genres in other dataframes.
for i in range(2004, 2023):
display(pd.read_csv('genre' + str(i) + '.csv', index_col=0))
| date | Role-Playing | Action RPG | Adventure | 3D | First-Person | Action Adventure | Linear | Action | Platformer | ... | On-foot | Tank | Wakeboarding | Futuristic Sub | Old Jet | Board / Card Game | Massively Multiplayer Online | Surf / Wakeboard | Breeding/Constructing | Rally / Offroad | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2004-01-04 | 80.0 | 0.792746 | 2.510363 | 79.585987 | 6.982397 | 1.189119 | 0.000000 | 3.303109 | 3.567358 | ... | 0.0 | 9.248705 | 0.000000 | 0.792746 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| 1 | 2004-01-11 | 84.0 | 0.000000 | 3.038860 | 74.713376 | 7.837385 | 0.396373 | 1.056995 | 4.095855 | 1.981865 | ... | 0.0 | 8.852332 | 2.906736 | 0.000000 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| 2 | 2004-01-18 | 82.0 | 0.924870 | 2.510363 | 75.525478 | 8.264878 | 0.000000 | 0.000000 | 2.774611 | 3.170984 | ... | 0.0 | 10.966321 | 1.321244 | 0.000000 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| 3 | 2004-01-25 | 80.0 | 0.924870 | 2.774611 | 71.464968 | 7.694887 | 0.000000 | 1.453368 | 4.492228 | 1.717617 | ... | 0.0 | 8.852332 | 0.000000 | 0.000000 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| 4 | 2004-02-01 | 73.0 | 0.528497 | 2.246114 | 75.525478 | 6.412406 | 0.000000 | 0.660622 | 3.435233 | 2.378238 | ... | 0.0 | 8.059585 | 0.924870 | 0.000000 | 0.528497 | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 99 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 40.945611 | 0.0 | 0.0 | 0.0 |
| 100 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 40.452290 | 0.0 | 0.0 | 0.0 |
| 101 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 40.945611 | 0.0 | 0.0 | 0.0 |
| 102 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 49.332061 | 0.0 | 0.0 | 0.0 |
| 103 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 43.905534 | 0.0 | 0.0 | 0.0 |
104 rows × 163 columns
| date | Role-Playing | Action RPG | Adventure | 3D | First-Person | Action Adventure | Linear | Action | Platformer | ... | On-foot | Tank | Wakeboarding | Futuristic Sub | Old Jet | Board / Card Game | Massively Multiplayer Online | Surf / Wakeboard | Breeding/Constructing | Rally / Offroad | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2005-01-02 | 74.0 | 0.294404 | 5.593685 | 57.574054 | 9.862549 | 0.000000 | 0.588809 | 7.065707 | 3.091247 | ... | 0.000000 | 6.476898 | 0.000000 | 0.0 | 0.588809 | NaN | NaN | NaN | NaN | NaN |
| 1 | 2005-01-09 | 76.0 | 0.883213 | 4.857674 | 50.034595 | 8.096123 | 0.000000 | 0.000000 | 5.299280 | 2.796842 | ... | 0.588809 | 8.684932 | 0.294404 | 0.0 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| 2 | 2005-01-16 | 75.0 | 0.883213 | 4.121662 | 58.944865 | 5.740887 | 0.294404 | 1.324820 | 5.299280 | 2.060831 | ... | 0.736011 | 7.801718 | 0.000000 | 0.0 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| 3 | 2005-01-23 | 77.0 | 0.000000 | 4.563269 | 52.090811 | 8.096123 | 0.000000 | 0.588809 | 4.563269 | 2.796842 | ... | 0.000000 | 8.243325 | 0.294404 | 0.0 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| 4 | 2005-01-30 | 75.0 | 0.441607 | 3.238449 | 56.203243 | 10.745763 | 0.000000 | 0.294404 | 4.268865 | 2.355236 | ... | 0.000000 | 8.979336 | 0.000000 | 0.0 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 99 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 47.658031 | 0.0 | 0.0 | 0.0 |
| 100 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 49.616580 | 0.0 | 0.0 | 0.0 |
| 101 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 52.880829 | 0.0 | 0.0 | 0.0 |
| 102 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 65.284974 | 0.0 | 0.0 | 0.0 |
| 103 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 65.284974 | 0.0 | 0.0 | 0.0 |
104 rows × 163 columns
| date | Role-Playing | Action RPG | Adventure | 3D | First-Person | Action Adventure | Linear | Action | Platformer | ... | On-foot | Tank | Wakeboarding | Futuristic Sub | Old Jet | Board / Card Game | Massively Multiplayer Online | Surf / Wakeboard | Breeding/Constructing | Rally / Offroad | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2006-01-01 | 89.0 | 1.165394 | 4.273113 | 61.468421 | 10.682782 | 0.388465 | 0.388465 | 9.711620 | 3.301951 | ... | 0.0 | 8.740458 | 0.000000 | 0.000000 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| 1 | 2006-01-08 | 83.0 | 0.194232 | 4.661578 | 57.129474 | 9.323155 | 0.000000 | 0.582697 | 6.798134 | 2.913486 | ... | 0.0 | 9.711620 | 0.582697 | 0.000000 | 0.582697 | NaN | NaN | NaN | NaN | NaN |
| 2 | 2006-01-15 | 83.0 | 0.388465 | 3.496183 | 62.191579 | 9.905852 | 0.000000 | 0.582697 | 7.575064 | 3.496183 | ... | 0.0 | 10.488550 | 0.000000 | 0.000000 | 0.388465 | NaN | NaN | NaN | NaN | NaN |
| 3 | 2006-01-22 | 83.0 | 0.776930 | 5.050042 | 63.637895 | 9.323155 | 0.388465 | 0.388465 | 10.294317 | 2.136556 | ... | 0.0 | 11.265479 | 0.582697 | 0.194232 | 0.388465 | NaN | NaN | NaN | NaN | NaN |
| 4 | 2006-01-29 | 86.0 | 0.971162 | 6.409669 | 60.022105 | 10.682782 | 0.000000 | 0.000000 | 9.905852 | 3.301951 | ... | 0.0 | 11.459712 | 0.000000 | 0.388465 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 101 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 55.250000 | 0.0 | 0.0 | 0.0 |
| 102 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 57.375000 | 0.0 | 0.0 | 0.0 |
| 103 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 70.833333 | 0.0 | 0.0 | 0.0 |
| 104 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 67.291667 | 0.0 | 0.0 | 0.0 |
| 105 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 62.333333 | 0.0 | 0.0 | 0.0 |
106 rows × 163 columns
| date | Role-Playing | Action RPG | Adventure | 3D | First-Person | Action Adventure | Linear | Action | Platformer | ... | On-foot | Tank | Wakeboarding | Futuristic Sub | Old Jet | Board / Card Game | Massively Multiplayer Online | Surf / Wakeboard | Breeding/Constructing | Rally / Offroad | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2007-01-07 | 77.0 | 0.513863 | 5.652491 | 61.317757 | 10.303887 | 0.513863 | 0.856438 | 13.463064 | 2.740602 | ... | 0.000000 | 10.466041 | 0.171288 | 0.0 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| 1 | 2007-01-14 | 79.0 | 0.856438 | 5.823778 | 63.264352 | 10.487885 | 0.000000 | 0.342575 | 14.460328 | 3.939615 | ... | 0.342575 | 9.258421 | 0.000000 | 0.0 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| 2 | 2007-01-21 | 76.0 | 0.000000 | 5.138628 | 63.264352 | 10.855881 | 0.000000 | 1.370301 | 15.956224 | 2.911889 | ... | 0.000000 | 10.466041 | 0.000000 | 0.0 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| 3 | 2007-01-28 | 84.0 | 0.171288 | 4.282190 | 67.157543 | 12.143867 | 0.342575 | 0.342575 | 15.706908 | 3.254464 | ... | 0.171288 | 10.868581 | 0.000000 | 0.0 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| 4 | 2007-02-04 | 80.0 | 0.513863 | 5.823778 | 67.157543 | 10.855881 | 0.171288 | 0.685150 | 14.958960 | 2.740602 | ... | 0.000000 | 11.069851 | 0.513863 | 0.0 | 0.171288 | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 99 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 60.656682 | 0.0 | 0.0 | 0.0 |
| 100 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 68.744240 | 0.0 | 0.0 | 0.0 |
| 101 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 73.596774 | 0.0 | 0.0 | 0.0 |
| 102 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 80.875576 | 0.0 | 0.0 | 0.0 |
| 103 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 74.405530 | 0.0 | 0.0 | 0.0 |
104 rows × 163 columns
| date | Role-Playing | Action RPG | Adventure | 3D | First-Person | Action Adventure | Linear | Action | Platformer | ... | On-foot | Tank | Wakeboarding | Futuristic Sub | Old Jet | Board / Card Game | Massively Multiplayer Online | Surf / Wakeboard | Breeding/Constructing | Rally / Offroad | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2008-01-06 | 85.0 | 0.627771 | 6.905476 | 81.985135 | 15.066493 | 0.313885 | 0.627771 | 20.649762 | 4.080508 | ... | 0.0 | 16.267970 | 0.313885 | 0.000000 | 0.313885 | NaN | NaN | NaN | NaN | NaN |
| 1 | 2008-01-13 | 86.0 | 0.313885 | 8.788787 | 78.081081 | 13.810952 | 0.313885 | 0.313885 | 21.305310 | 4.080508 | ... | 0.0 | 18.819808 | 0.000000 | 0.000000 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| 2 | 2008-01-20 | 89.0 | 0.627771 | 8.474902 | 81.985135 | 15.066493 | 0.313885 | 0.627771 | 22.616406 | 4.394394 | ... | 0.0 | 17.862868 | 0.000000 | 0.313885 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| 3 | 2008-01-27 | 92.0 | 0.627771 | 8.474902 | 79.382432 | 14.124837 | 0.313885 | 0.627771 | 23.271954 | 4.708279 | ... | 0.0 | 18.181848 | 0.313885 | 0.000000 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| 4 | 2008-02-03 | 89.0 | 0.941656 | 8.788787 | 80.683784 | 14.124837 | 0.313885 | 0.627771 | 22.944180 | 7.533246 | ... | 0.0 | 18.181848 | 0.000000 | 0.313885 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 99 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 65.630162 | 0.0 | 0.0 | 0.0 |
| 100 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 72.725314 | 0.0 | 0.0 | 0.0 |
| 101 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 71.838420 | 0.0 | 0.0 | 0.0 |
| 102 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 88.689408 | 0.0 | 0.0 | 0.0 |
| 103 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 86.028725 | 0.0 | 0.0 | 0.0 |
104 rows × 163 columns
| date | Role-Playing | Action RPG | Adventure | 3D | First-Person | Action Adventure | Linear | Action | Platformer | ... | On-foot | Tank | Wakeboarding | Futuristic Sub | Old Jet | Board / Card Game | Massively Multiplayer Online | Surf / Wakeboard | Breeding/Constructing | Rally / Offroad | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2009-01-04 | 80.0 | 0.591931 | 10.950718 | 108.889098 | 15.982128 | 0.591931 | 0.591931 | 30.221198 | 6.215272 | ... | 0.0 | 30.856064 | 0.000000 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 1 | 2009-01-11 | 85.0 | 0.591931 | 10.062822 | 112.998120 | 15.390198 | 0.295965 | 0.295965 | 32.739631 | 4.735445 | ... | 0.0 | 32.159841 | 0.295965 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 2 | 2009-01-18 | 88.0 | 0.887896 | 12.134579 | 121.216165 | 16.574059 | 0.295965 | 0.887896 | 38.196237 | 5.919307 | ... | 0.0 | 33.029026 | 0.295965 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 3 | 2009-01-25 | 82.0 | 0.887896 | 13.022475 | 110.943609 | 17.165990 | 0.887896 | 0.591931 | 37.776498 | 6.511237 | ... | 0.0 | 31.290656 | 0.000000 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 4 | 2009-02-01 | 85.0 | 0.887896 | 12.726510 | 123.270677 | 17.461955 | 0.000000 | 0.591931 | 35.677803 | 5.919307 | ... | 0.0 | 30.421471 | 0.000000 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 99 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 69.733503 | 0.0 | 0.0 | 0.0 |
| 100 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 69.733503 | 0.0 | 0.0 | 0.0 |
| 101 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 69.733503 | 0.0 | 0.0 | 0.0 |
| 102 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 92.978003 | 0.0 | 0.0 | 0.0 |
| 103 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 85.539763 | 0.0 | 0.0 | 0.0 |
104 rows × 163 columns
| date | Role-Playing | Action RPG | Adventure | 3D | First-Person | Action Adventure | Linear | Action | Platformer | ... | On-foot | Tank | Wakeboarding | Futuristic Sub | Old Jet | Board / Card Game | Massively Multiplayer Online | Surf / Wakeboard | Breeding/Constructing | Rally / Offroad | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2010-01-03 | 93.0 | 0.741635 | 20.024136 | 207.807407 | 22.990675 | 0.741635 | 0.741635 | 43.050383 | 8.157981 | ... | 0.0 | 44.936416 | 0.370817 | 0.000000 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 1 | 2010-01-10 | 90.0 | 0.741635 | 18.170049 | 210.311111 | 20.765771 | 0.741635 | 0.741635 | 39.780734 | 8.528799 | ... | 0.0 | 47.378613 | 0.370817 | 0.000000 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 2 | 2010-01-17 | 91.0 | 0.741635 | 17.799232 | 217.822222 | 22.619857 | 0.741635 | 0.741635 | 43.595324 | 8.157981 | ... | 0.0 | 44.936416 | 0.000000 | 0.000000 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 3 | 2010-01-24 | 88.0 | 1.112452 | 18.911684 | 220.325926 | 21.878223 | 0.741635 | 0.741635 | 48.499798 | 8.899616 | ... | 0.0 | 48.843931 | 0.000000 | 0.370817 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 4 | 2010-01-31 | 90.0 | 0.741635 | 20.024136 | 227.837037 | 22.249040 | 0.370817 | 1.112452 | 45.230149 | 8.157981 | ... | 0.0 | 46.401734 | 0.370817 | 0.000000 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 99 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 71.208275 | 0.0 | 0.0 | 0.0 |
| 100 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 70.232819 | 0.0 | 0.0 | 0.0 |
| 101 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 76.085554 | 0.0 | 0.0 | 0.0 |
| 102 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 88.766480 | 0.0 | 0.0 | 0.0 |
| 103 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 84.864656 | 0.0 | 0.0 | 0.0 |
104 rows × 163 columns
| date | Role-Playing | Action RPG | Adventure | 3D | First-Person | Action Adventure | Linear | Action | Platformer | ... | On-foot | Tank | Wakeboarding | Futuristic Sub | Old Jet | Board / Card Game | Massively Multiplayer Online | Surf / Wakeboard | Breeding/Constructing | Rally / Offroad | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2011-01-02 | 97.0 | 1.392702 | 25.068636 | 284.815490 | 25.532870 | 0.464234 | 0.928468 | 39.459890 | 9.284680 | ... | 0.0 | 54.468230 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 1 | 2011-01-09 | 93.0 | 2.321170 | 25.068636 | 273.861048 | 24.604402 | 0.928468 | 0.928468 | 36.210252 | 7.891978 | ... | 0.0 | 51.200136 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 2 | 2011-01-16 | 92.0 | 2.321170 | 25.532870 | 284.815490 | 25.532870 | 0.928468 | 1.392702 | 41.781060 | 8.356212 | ... | 0.0 | 51.744818 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 3 | 2011-01-23 | 98.0 | 1.392702 | 26.461338 | 292.118451 | 25.532870 | 0.928468 | 1.392702 | 41.316826 | 9.748914 | ... | 0.0 | 49.021407 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 4 | 2011-01-30 | 100.0 | 0.928468 | 25.532870 | 314.027335 | 25.068636 | 0.928468 | 1.392702 | 40.388358 | 9.284680 | ... | 0.0 | 47.932042 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 99 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 62.397880 | 0.0 | 0.0 | 0.0 |
| 100 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 66.776678 | 0.0 | 0.0 | 0.0 |
| 101 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 66.776678 | 0.0 | 0.0 | 0.0 |
| 102 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 79.913074 | 0.0 | 0.0 | 0.0 |
| 103 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 79.913074 | 0.0 | 0.0 | 0.0 |
104 rows × 163 columns
| date | Role-Playing | Action RPG | Adventure | 3D | First-Person | Action Adventure | Linear | Action | Platformer | ... | On-foot | Tank | Wakeboarding | Futuristic Sub | Old Jet | Board / Card Game | Massively Multiplayer Online | Surf / Wakeboard | Breeding/Constructing | Rally / Offroad | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2012-01-01 | 91.0 | 1.348214 | 35.952381 | 357.971487 | 25.166667 | 1.348214 | 0.898810 | 45.288447 | 9.43750 | ... | 0.0 | 46.259893 | 0.0 | 0.0 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| 1 | 2012-01-08 | 85.0 | 1.348214 | 29.211310 | 346.900204 | 24.717262 | 1.348214 | 1.348214 | 45.750574 | 8.53869 | ... | 0.0 | 44.872096 | 0.0 | 0.0 | 0.449405 | NaN | NaN | NaN | NaN | NaN |
| 2 | 2012-01-15 | 85.0 | 1.348214 | 30.559524 | 346.900204 | 24.267857 | 1.348214 | 1.348214 | 45.750574 | 9.43750 | ... | 0.0 | 44.409497 | 0.0 | 0.0 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| 3 | 2012-01-22 | 91.0 | 1.348214 | 31.458333 | 328.448065 | 25.616071 | 1.348214 | 1.797619 | 45.750574 | 9.43750 | ... | 0.0 | 43.946898 | 0.0 | 0.0 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| 4 | 2012-01-29 | 85.0 | 1.348214 | 28.761905 | 343.209776 | 25.616071 | 1.797619 | 1.348214 | 45.750574 | 8.53869 | ... | 0.0 | 45.334695 | 0.0 | 0.0 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 101 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 65.165208 | 0.0 | 0.0 | 0.0 |
| 102 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 68.040144 | 0.0 | 0.0 | 0.0 |
| 103 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 75.706639 | 0.0 | 0.0 | 0.0 |
| 104 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 87.206382 | 0.0 | 0.0 | 0.0 |
| 105 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 80.498199 | 0.0 | 0.0 | 0.0 |
106 rows × 163 columns
| date | Role-Playing | Action RPG | Adventure | 3D | First-Person | Action Adventure | Linear | Action | Platformer | ... | On-foot | Tank | Wakeboarding | Futuristic Sub | Old Jet | Board / Card Game | Massively Multiplayer Online | Surf / Wakeboard | Breeding/Constructing | Rally / Offroad | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2013-01-06 | 85.0 | 1.213918 | 25.492268 | 315.087760 | 28.729381 | 0.809278 | 1.213918 | 41.060155 | 8.497423 | ... | 0.0 | 38.861386 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 1 | 2013-01-13 | 93.0 | 2.023196 | 25.492268 | 303.122402 | 28.729381 | 0.809278 | 1.213918 | 44.028359 | 9.306701 | ... | 0.0 | 38.343234 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 2 | 2013-01-20 | 92.0 | 1.618557 | 25.087629 | 315.087760 | 27.515464 | 0.809278 | 1.213918 | 45.512461 | 8.902062 | ... | 0.0 | 43.006601 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 3 | 2013-01-27 | 92.0 | 1.213918 | 26.301546 | 315.087760 | 27.920103 | 0.809278 | 1.213918 | 45.017760 | 8.497423 | ... | 0.0 | 40.415842 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 4 | 2013-02-03 | 91.0 | 1.618557 | 26.301546 | 319.076212 | 26.706186 | 0.809278 | 2.023196 | 45.017760 | 10.115979 | ... | 0.0 | 42.488449 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 99 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 56.047970 | 0.0 | 0.0 | 0.0 |
| 100 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 63.398524 | 0.0 | 0.0 | 0.0 |
| 101 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 68.911439 | 0.0 | 0.0 | 0.0 |
| 102 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 80.856089 | 0.0 | 0.0 | 0.0 |
| 103 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 72.586716 | 0.0 | 0.0 | 0.0 |
104 rows × 163 columns
| date | Role-Playing | Action RPG | Adventure | 3D | First-Person | Action Adventure | Linear | Action | Platformer | ... | On-foot | Tank | Wakeboarding | Futuristic Sub | Old Jet | Board / Card Game | Massively Multiplayer Online | Surf / Wakeboard | Breeding/Constructing | Rally / Offroad | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2014-01-05 | 99.0 | 1.977717 | 24.721466 | 373.271028 | 32.137905 | 0.988859 | 1.977717 | 43.015350 | 8.899728 | ... | 0.0 | 53.407499 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 1 | 2014-01-12 | 92.0 | 2.472147 | 22.249319 | 365.805607 | 32.137905 | 0.988859 | 1.483288 | 39.059916 | 8.899728 | ... | 0.0 | 47.901572 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 2 | 2014-01-19 | 98.0 | 1.977717 | 21.754890 | 365.805607 | 34.115623 | 0.988859 | 1.977717 | 37.576628 | 7.910869 | ... | 0.0 | 52.306314 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 3 | 2014-01-26 | 100.0 | 1.977717 | 24.721466 | 373.271028 | 34.610052 | 0.988859 | 1.977717 | 39.059916 | 8.899728 | ... | 0.0 | 51.755721 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 4 | 2014-02-02 | 100.0 | 2.472147 | 22.743748 | 362.072897 | 35.104481 | 0.494429 | 1.977717 | 38.071057 | 7.910869 | ... | 0.0 | 54.508685 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 99 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 55.402355 | 0.0 | 0.0 | 0.0 |
| 100 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 56.151035 | 0.0 | 0.0 | 0.0 |
| 101 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 59.145757 | 0.0 | 0.0 | 0.0 |
| 102 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 59.145757 | 0.0 | 0.0 | 0.0 |
| 103 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 66.632562 | 0.0 | 0.0 | 0.0 |
104 rows × 163 columns
| date | Role-Playing | Action RPG | Adventure | 3D | First-Person | Action Adventure | Linear | Action | Platformer | ... | On-foot | Tank | Wakeboarding | Futuristic Sub | Old Jet | Board / Card Game | Massively Multiplayer Online | Surf / Wakeboard | Breeding/Constructing | Rally / Offroad | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2015-01-04 | 94.0 | 1.751024 | 22.179632 | 265.557598 | 36.771494 | 0.583675 | 2.334698 | 34.436796 | 9.922467 | ... | 0.0 | 56.528869 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 1 | 2015-01-11 | 85.0 | 1.751024 | 19.261259 | 271.148284 | 36.187820 | 1.167349 | 2.334698 | 34.436796 | 8.171443 | ... | 0.0 | 50.515160 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 2 | 2015-01-18 | 89.0 | 2.334698 | 19.844933 | 257.171569 | 36.771494 | 1.167349 | 1.751024 | 38.522518 | 9.338792 | ... | 0.0 | 49.913789 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 3 | 2015-01-25 | 89.0 | 1.751024 | 19.261259 | 273.943627 | 36.771494 | 1.167349 | 2.334698 | 40.273541 | 7.587769 | ... | 0.0 | 58.934353 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 4 | 2015-02-01 | 87.0 | 1.751024 | 19.261259 | 268.352941 | 37.355169 | 0.583675 | 2.334698 | 35.020471 | 8.171443 | ... | 0.0 | 60.137095 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 99 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 47.561350 | 0.0 | 0.0 | 0.0 |
| 100 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 62.509202 | 0.0 | 0.0 | 0.0 |
| 101 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 49.599693 | 0.0 | 0.0 | 0.0 |
| 102 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 64.547546 | 0.0 | 0.0 | 0.0 |
| 103 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 63.868098 | 0.0 | 0.0 | 0.0 |
104 rows × 163 columns
| date | Role-Playing | Action RPG | Adventure | 3D | First-Person | Action Adventure | Linear | Action | Platformer | ... | On-foot | Tank | Wakeboarding | Futuristic Sub | Old Jet | Board / Card Game | Massively Multiplayer Online | Surf / Wakeboard | Breeding/Constructing | Rally / Offroad | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2016-01-03 | 100.0 | 2.483432 | 21.523077 | 202.313811 | 43.046154 | 0.827811 | 2.483432 | 30.628994 | 9.105917 | ... | 0.0 | 55.463314 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 1 | 2016-01-10 | 95.0 | 2.483432 | 21.523077 | 198.267534 | 42.218343 | 0.827811 | 2.483432 | 30.628994 | 7.450296 | ... | 0.0 | 57.118935 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 2 | 2016-01-17 | 99.0 | 2.483432 | 19.039645 | 202.313811 | 38.907101 | 0.827811 | 2.483432 | 34.768047 | 7.450296 | ... | 0.0 | 57.118935 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 3 | 2016-01-24 | 93.0 | 2.483432 | 19.867456 | 198.267534 | 39.734911 | 0.827811 | 2.483432 | 33.940237 | 9.105917 | ... | 0.0 | 63.741420 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 4 | 2016-01-31 | 94.0 | 2.483432 | 21.523077 | 198.267534 | 40.562722 | 0.827811 | 2.483432 | 33.112426 | 7.450296 | ... | 0.0 | 58.774556 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 99 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 47.370175 | 0.0 | 0.0 | 0.0 |
| 100 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 54.475701 | 0.0 | 0.0 | 0.0 |
| 101 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 55.265204 | 0.0 | 0.0 | 0.0 |
| 102 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 60.791725 | 0.0 | 0.0 | 0.0 |
| 103 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 60.791725 | 0.0 | 0.0 | 0.0 |
104 rows × 163 columns
| date | Role-Playing | Action RPG | Adventure | 3D | First-Person | Action Adventure | Linear | Action | Platformer | ... | On-foot | Tank | Wakeboarding | Futuristic Sub | Old Jet | Board / Card Game | Massively Multiplayer Online | Surf / Wakeboard | Breeding/Constructing | Rally / Offroad | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2017-01-01 | 95.0 | 3.364341 | 20.186047 | 211.161435 | 60.558140 | 0.672868 | 2.691473 | 28.933333 | 9.420155 | ... | 0.0 | 66.013266 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 1 | 2017-01-08 | 100.0 | 3.364341 | 18.840310 | 195.267564 | 57.193798 | 0.672868 | 2.691473 | 26.914729 | 9.420155 | ... | 0.0 | 65.318390 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 2 | 2017-01-15 | 98.0 | 2.691473 | 18.840310 | 199.808670 | 52.483721 | 0.672868 | 4.037209 | 26.914729 | 9.420155 | ... | 0.0 | 63.928637 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 3 | 2017-01-22 | 88.0 | 2.691473 | 18.167442 | 195.267564 | 54.502326 | 1.345736 | 4.037209 | 27.587597 | 8.747287 | ... | 0.0 | 69.487649 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 4 | 2017-01-29 | 91.0 | 3.364341 | 18.840310 | 188.455904 | 54.502326 | 0.672868 | 4.037209 | 27.587597 | 8.747287 | ... | 0.0 | 66.013266 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 101 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 52.621679 | 0.0 | 0.0 | 0.0 |
| 102 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 51.920056 | 0.0 | 0.0 | 0.0 |
| 103 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 54.024924 | 0.0 | 0.0 | 0.0 |
| 104 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 60.339525 | 0.0 | 0.0 | 0.0 |
| 105 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 54.024924 | 0.0 | 0.0 | 0.0 |
106 rows × 163 columns
| date | Role-Playing | Action RPG | Adventure | 3D | First-Person | Action Adventure | Linear | Action | Platformer | ... | On-foot | Tank | Wakeboarding | Futuristic Sub | Old Jet | Board / Card Game | Massively Multiplayer Online | Surf / Wakeboard | Breeding/Constructing | Rally / Offroad | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2018-01-07 | 98.0 | 2.526523 | 14.316964 | 169.234828 | 57.267857 | 0.842174 | 4.210872 | 20.212185 | 10.106092 | ... | 0.0 | 58.952206 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 1 | 2018-01-14 | 98.0 | 2.526523 | 17.685662 | 157.388391 | 55.583508 | 1.684349 | 3.368697 | 19.370011 | 8.421744 | ... | 0.0 | 62.320903 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 2 | 2018-01-21 | 95.0 | 3.368697 | 16.001313 | 167.542480 | 56.425683 | 0.842174 | 5.053046 | 19.370011 | 11.790441 | ... | 0.0 | 64.847426 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 3 | 2018-01-28 | 99.0 | 3.368697 | 16.001313 | 152.311346 | 55.583508 | 0.842174 | 5.053046 | 20.212185 | 10.106092 | ... | 0.0 | 65.689601 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 4 | 2018-02-04 | 92.0 | 3.368697 | 16.001313 | 143.849604 | 53.899160 | 1.684349 | 4.210872 | 18.527836 | 10.948267 | ... | 0.0 | 61.478729 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 99 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 43.545774 | 0.0 | 0.0 | 0.0 |
| 100 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 42.674858 | 0.0 | 0.0 | 0.0 |
| 101 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 45.287605 | 0.0 | 0.0 | 0.0 |
| 102 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 51.384013 | 0.0 | 0.0 | 0.0 |
| 103 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 48.771267 | 0.0 | 0.0 | 0.0 |
104 rows × 163 columns
| date | Role-Playing | Action RPG | Adventure | 3D | First-Person | Action Adventure | Linear | Action | Platformer | ... | On-foot | Tank | Wakeboarding | Futuristic Sub | Old Jet | Board / Card Game | Massively Multiplayer Online | Surf / Wakeboard | Breeding/Constructing | Rally / Offroad | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2019-01-06 | 73.0 | 2.583676 | 13.900968 | 106.838279 | 35.525551 | 0.661951 | 2.583676 | 13.900968 | 7.943410 | ... | 0.0 | 38.393150 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 1 | 2019-01-13 | 73.0 | 3.875515 | 11.915115 | 118.709199 | 35.525551 | 0.661951 | 2.583676 | 15.886821 | 9.929263 | ... | 0.0 | 41.040953 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 2 | 2019-01-20 | 76.0 | 2.583676 | 11.915115 | 102.881306 | 34.879632 | 0.661951 | 2.583676 | 13.239017 | 7.281459 | ... | 0.0 | 42.364855 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 3 | 2019-01-27 | 75.0 | 3.875515 | 13.900968 | 102.881306 | 29.712279 | 0.661951 | 3.229596 | 15.224870 | 6.619509 | ... | 0.0 | 44.350707 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 4 | 2019-02-03 | 73.0 | 2.583676 | 13.239017 | 110.795252 | 32.941875 | 0.661951 | 3.229596 | 13.900968 | 6.619509 | ... | 0.0 | 40.379002 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 99 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 27.904028 | 0.0 | 0.0 | 0.0 |
| 100 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 35.042268 | 0.0 | 0.0 | 0.0 |
| 101 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 34.393337 | 0.0 | 0.0 | 0.0 |
| 102 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 40.233715 | 0.0 | 0.0 | 0.0 |
| 103 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 35.691198 | 0.0 | 0.0 | 0.0 |
104 rows × 163 columns
| date | Role-Playing | Action RPG | Adventure | 3D | First-Person | Action Adventure | Linear | Action | Platformer | ... | On-foot | Tank | Wakeboarding | Futuristic Sub | Old Jet | Board / Card Game | Massively Multiplayer Online | Surf / Wakeboard | Breeding/Constructing | Rally / Offroad | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2020-01-05 | 74.0 | 2.858475 | 11.433898 | 115.175610 | 38.112994 | 1.905650 | 3.811299 | 13.339548 | 8.575424 | ... | 0.0 | 40.018644 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 1 | 2020-01-12 | 76.0 | 2.858475 | 11.433898 | 120.660163 | 39.065819 | 0.952825 | 2.858475 | 13.339548 | 8.575424 | ... | 0.0 | 43.829944 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 2 | 2020-01-19 | 76.0 | 2.858475 | 11.433898 | 120.660163 | 35.254520 | 0.952825 | 3.811299 | 14.292373 | 9.528249 | ... | 0.0 | 44.782768 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 3 | 2020-01-26 | 70.0 | 2.858475 | 11.433898 | 115.175610 | 40.018644 | 0.952825 | 3.811299 | 15.245198 | 9.528249 | ... | 0.0 | 44.782768 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| 4 | 2020-02-02 | 74.0 | 2.858475 | 11.433898 | 112.433333 | 39.065819 | 0.952825 | 4.764124 | 12.386723 | 8.575424 | ... | 0.0 | 40.018644 | 0.0 | 0.0 | 0.0 | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 99 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 30.927042 | 0.0 | 0.0 | 0.0 |
| 100 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 31.864225 | 0.0 | 0.0 | 0.0 |
| 101 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 38.424507 | 0.0 | 0.0 | 0.0 |
| 102 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 40.298873 | 0.0 | 0.0 | 0.0 |
| 103 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 39.361690 | 0.0 | 0.0 | 0.0 |
104 rows × 163 columns
| date | Role-Playing | Action RPG | Adventure | 3D | First-Person | Action Adventure | Linear | Action | Platformer | ... | On-foot | Tank | Wakeboarding | Futuristic Sub | Old Jet | Board / Card Game | Massively Multiplayer Online | Surf / Wakeboard | Breeding/Constructing | Rally / Offroad | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2021-01-03 | 90.0 | 3.396904 | 12.738389 | 179.274255 | 63.213224 | 1.698452 | 4.329673 | 16.452757 | 13.587615 | ... | 0.0 | 51.802782 | 0.0 | 0.0 | 0.849226 | NaN | NaN | NaN | NaN | NaN |
| 1 | 2021-01-10 | 92.0 | 3.396904 | 12.738389 | 202.406417 | 66.676962 | 0.849226 | 4.329673 | 15.586822 | 14.436841 | ... | 0.0 | 51.802782 | 0.0 | 0.0 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| 2 | 2021-01-17 | 89.0 | 3.396904 | 12.738389 | 179.274255 | 63.213224 | 0.849226 | 5.195607 | 15.586822 | 12.738389 | ... | 0.0 | 50.104330 | 0.0 | 0.0 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| 3 | 2021-01-24 | 88.0 | 3.396904 | 13.587615 | 185.057296 | 64.079158 | 0.849226 | 4.329673 | 18.184626 | 13.587615 | ... | 0.0 | 47.556652 | 0.0 | 0.0 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| 4 | 2021-01-31 | 96.0 | 3.396904 | 13.587615 | 193.731856 | 61.481354 | 0.849226 | 5.195607 | 15.586822 | 14.436841 | ... | 0.0 | 48.405878 | 0.0 | 0.0 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 99 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 29.803034 | 0.0 | 0.0 | 0.0 |
| 100 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 30.548110 | 0.0 | 0.0 | 0.0 |
| 101 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 30.548110 | 0.0 | 0.0 | 0.0 |
| 102 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 32.038261 | 0.0 | 0.0 | 0.0 |
| 103 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 39.489020 | 0.0 | 0.0 | 0.0 |
104 rows × 163 columns
| date | Role-Playing | Action RPG | Adventure | 3D | First-Person | Action Adventure | Linear | Action | Platformer | ... | On-foot | Tank | Wakeboarding | Futuristic Sub | Old Jet | Board / Card Game | Massively Multiplayer Online | Surf / Wakeboard | Breeding/Constructing | Rally / Offroad | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2022-01-02 | 88.0 | 3.934219 | 12.589500 | 165.402379 | 66.881720 | 0.786844 | 4.721063 | 14.163188 | 15.736875 | ... | 0.0 | 46.423782 | 0.0 | 0.0 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| 1 | 2022-01-09 | 93.0 | 3.934219 | 12.589500 | 156.696991 | 60.586970 | 1.573688 | 4.721063 | 14.163188 | 11.802657 | ... | 0.0 | 44.850095 | 0.0 | 0.0 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| 2 | 2022-01-16 | 90.0 | 3.147375 | 11.802657 | 149.732680 | 60.586970 | 0.786844 | 4.721063 | 13.376344 | 13.376344 | ... | 0.0 | 42.489564 | 0.0 | 0.0 | 0.786844 | NaN | NaN | NaN | NaN | NaN |
| 3 | 2022-01-23 | 88.0 | 3.934219 | 13.376344 | 161.920224 | 62.160658 | 1.573688 | 6.294750 | 14.163188 | 13.376344 | ... | 0.0 | 46.423782 | 0.0 | 0.0 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| 4 | 2022-01-30 | 81.0 | 3.934219 | 12.589500 | 156.696991 | 61.373814 | 0.786844 | 6.294750 | 13.376344 | 11.802657 | ... | 0.0 | 47.210626 | 0.0 | 0.0 | 0.000000 | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 69 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 52.751880 | 0.0 | 0.0 | 0.0 |
| 70 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 51.927632 | 0.0 | 0.0 | 0.0 |
| 71 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 42.860902 | 0.0 | 0.0 | 0.0 |
| 72 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 40.388158 | 0.0 | 0.0 | 0.0 |
| 73 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | 0.0 | 37.091165 | 0.0 | 0.0 | 0.0 |
74 rows × 163 columns
This dataframe was created using the interest over time graph of google trends. The date columns shows the date for each row. Each subsequent component shows the proportional amount of searches done over time for the column name. This was done by comparing each value with a 'yardstick', another keyword not a genre, and scaling each graph to allow the yardstick to be same through out. This dataframe was used to create another dataframe, which contains the top results. Each dataframe is for the values for different years.
pd.read_csv('yearlygenre.csv', index_col=0)
| genre | Searches | year | Code | |
|---|---|---|---|---|
| 0 | Puzzle | 408.088057 | 2022 | /m/0lvmz |
| 1 | Board Games | 244.155928 | 2022 | /m/015ll |
| 2 | Team | 163.794808 | 2022 | Team |
| 3 | Football | 153.767703 | 2022 | Football |
| 4 | 3D | 152.791330 | 2022 | 3D |
| ... | ... | ... | ... | ... |
| 10 | Flight | 38.635414 | 2004 | Flight |
| 11 | Massively Multiplayer Online | 38.460034 | 2004 | /m/057m6 |
| 12 | Football | 34.212880 | 2004 | Football |
| 13 | Golf | 33.556555 | 2004 | Golf |
| 14 | Board Games | 32.885340 | 2004 | /m/015ll |
285 rows × 4 columns
This dataframe was created by combining the previous dataframes together. The genre column contains the top 15 genre with the highest mean search count over the year for all the dataframes; Searches column contains the mean stated before; year contains the year these results were from; Code column contains the google trends code, and a name if the genre has no code. This dataframe was mainly used for the analysis of the Searches column
for i in range(2004, 2023):
display(pd.read_csv('genrecountry' + str(i) + '.csv', index_col=0))
| Puzzle | Role-Playing | Tycoon | 3D | Trainer | Sports | Street | Music | Combat | Command | Flight | Massively Multiplayer Online | Football | Golf | Board Games | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||
| Afghanistan | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Albania | 65.0 | 0.000000 | 0.000000 | 36.428571 | 67.941176 | 0.0 | 0.000000 | 0.000000 | 32.307692 | 0.0 | 0.0 | 0.0 | 0.0 | 35.0 | 0.0 |
| Algeria | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| American Samoa | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Andorra | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Yemen | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Zambia | 0.0 | 53.846154 | 257.142857 | 0.000000 | 0.000000 | 0.0 | 69.491525 | 96.078431 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| Zimbabwe | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Åland Islands | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
250 rows × 15 columns
| Puzzle | Role-Playing | 3D | Tycoon | Street | Football | Massively Multiplayer Online | Trainer | Music | Sports | Combat | Flight | Golf | Racing | Board Games | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||
| Afghanistan | 61.0 | 0.0 | 156.0 | 0.0 | 0.0 | 0.0 | 0.0 | 53.857143 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| Albania | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Algeria | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| American Samoa | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Andorra | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Yemen | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Zambia | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Zimbabwe | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Åland Islands | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
250 rows × 15 columns
| Puzzle | Role-Playing | Tycoon | Massively Multiplayer Online | 3D | Football | Street | Music | Flight | Trainer | Racing | Sports | Combat | Virtual | Command | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||
| Afghanistan | 60.0 | 0.0 | NaN | 0.0 | 35.471698 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 46.956522 | 81.212121 | 0.0 |
| Albania | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Algeria | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| American Samoa | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Andorra | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Yemen | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Zambia | 55.0 | 0.0 | 45.0 | 0.0 | 0.000000 | 20.217391 | 0.0 | 33.947368 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 15.810811 | 0.0 |
| Zimbabwe | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Åland Islands | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
250 rows × 15 columns
| Puzzle | Role-Playing | Street | 3D | Racing | Massively Multiplayer Online | Football | Tycoon | Trainer | Command | Music | Sports | Virtual | Team | Flight | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||
| Afghanistan | 61.0 | 117.0 | 79.181818 | 40.591837 | 47.666667 | 0.0 | 0.0 | 0.0 | 47.666667 | 0.0 | 111.0 | 156.0 | 0.0 | 0.0 | 0.0 |
| Albania | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Algeria | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| American Samoa | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Andorra | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Yemen | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Zambia | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Zimbabwe | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Åland Islands | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
250 rows × 15 columns
| Puzzle | Racing | 3D | Role-Playing | Street | Massively Multiplayer Online | Football | Trainer | Shooter | Music | Tycoon | Team | Fighting | Space | Pet | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||
| Afghanistan | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Albania | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Algeria | 96.0 | 129.333333 | 396.000000 | 29.333333 | 196.000000 | 32.363636 | 96.000000 | 21.0 | 17.052632 | 129.333333 | 22.666667 | 36.000000 | 396.000000 | 21.0 | 3.547170 |
| American Samoa | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Andorra | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Yemen | 73.0 | 0.000000 | 73.000000 | 0.000000 | 45.972973 | 0.000000 | 0.000000 | 85.5 | 0.000000 | 23.000000 | 0.000000 | 28.102041 | 69.428571 | 0.0 | 21.214286 |
| Zambia | 49.0 | 49.000000 | 73.390244 | 21.857143 | 41.727273 | 20.830986 | 0.000000 | 0.0 | 27.461538 | 0.000000 | 0.000000 | 29.952381 | 0.000000 | 0.0 | 0.000000 |
| Zimbabwe | 70.0 | 120.000000 | 51.081081 | 30.000000 | 51.081081 | 16.875000 | 22.631579 | 0.0 | 20.000000 | 53.333333 | 0.000000 | 0.000000 | 28.823529 | 0.0 | 0.000000 |
| Åland Islands | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
250 rows × 15 columns
| Puzzle | 3D | Racing | Street | Shooter | Role-Playing | Massively Multiplayer Online | Fighting | Trainer | Football | Tycoon | Sports | Pet | Space | Team | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||
| Afghanistan | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Albania | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Algeria | 98.0 | 198.0 | 98.0 | 198.0 | 23.0 | 26.571429 | 38.0 | inf | 20.222222 | 98.0 | 20.222222 | 23.0 | 8.0 | 23.0 | 26.571429 |
| American Samoa | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Andorra | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Yemen | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Zambia | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Zimbabwe | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Åland Islands | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
250 rows × 15 columns
| 3D | Puzzle | Racing | Shooter | Street | Fighting | Football | Role-Playing | Massively Multiplayer Online | Trainer | Defense | Team | Sports | Music | Pet | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||
| Afghanistan | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Albania | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Algeria | NaN | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 |
| American Samoa | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Andorra | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Yemen | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Zambia | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Zimbabwe | 50.0 | 0.0 | 48.039216 | 0.0 | 46.153846 | 0.0 | 0.0 | 0.0 | 0.0 | 23.529412 | 0.0 | 54.166667 | 0.0 | 48.039216 | 0.0 |
| Åland Islands | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
250 rows × 15 columns
| 3D | Puzzle | Racing | Shooter | Street | Fighting | Team | Space | Defense | Football | Role-Playing | Massively Multiplayer Online | Trainer | Sports | Wargame | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||
| Afghanistan | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Albania | 95.0 | 120.000000 | 95.000000 | 21.315789 | 45.000000 | 15.833333 | 20.000000 | 12.857143 | 21.315789 | 66.428571 | 13.518519 | 15.000000 | 36.666667 | 40.454545 | 12.241379 |
| Algeria | 99.0 | 32.333333 | 32.333333 | 11.500000 | 49.000000 | 99.000000 | 8.090909 | 11.500000 | 4.263158 | 99.000000 | 8.090909 | 10.111111 | 9.000000 | 6.142857 | 99.000000 |
| American Samoa | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Andorra | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | NaN | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| Yemen | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Zambia | 71.0 | 102.818182 | 87.000000 | 23.727273 | 49.378378 | 13.647059 | 11.277778 | 21.000000 | 0.000000 | 116.000000 | 0.000000 | 0.000000 | 34.043478 | 56.294118 | 0.000000 |
| Zimbabwe | 82.0 | 57.000000 | 162.000000 | 33.428571 | 67.714286 | 25.902439 | 9.692308 | 13.034483 | 0.000000 | 60.260870 | 0.000000 | 0.000000 | 11.508197 | 44.068966 | 0.000000 |
| Åland Islands | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
250 rows × 15 columns
| 3D | Puzzle | Racing | Shooter | Team | Street | Defense | Fighting | Football | Space | Role-Playing | Massively Multiplayer Online | Sports | Wargame | Trainer | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||
| Afghanistan | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Albania | 97.0 | 97.000000 | 72.0 | 22.000000 | 12.000000 | 39.857143 | 22.000000 | 12.789474 | 72.0 | 10.636364 | 10.636364 | 6.090909 | 27.000000 | 11.285714 | 24.272727 |
| Algeria | NaN | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| American Samoa | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Andorra | 65.0 | 52.500000 | 0.0 | 0.000000 | 18.030303 | 22.377049 | 10.454545 | 0.000000 | 0.0 | 24.322034 | 48.333333 | NaN | 29.814815 | NaN | 0.000000 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Yemen | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Zambia | 92.0 | 34.105263 | 72.0 | 16.242424 | 64.727273 | 42.000000 | 0.000000 | 21.629630 | 152.0 | 13.052632 | 11.512195 | 0.000000 | 49.142857 | 0.000000 | 8.000000 |
| Zimbabwe | 94.0 | 48.545455 | 144.0 | 15.428571 | 14.689655 | 79.714286 | 4.526316 | 15.428571 | 54.0 | 5.764706 | 5.320755 | 0.000000 | 25.578947 | 5.764706 | 12.181818 |
| Åland Islands | 0.0 | 194.117647 | 0.0 | 0.000000 | 92.307692 | 177.777778 | NaN | 0.000000 | 150.0 | 0.000000 | 0.000000 | 138.095238 | 0.000000 | 0.000000 | 0.000000 |
250 rows × 15 columns
| 3D | Puzzle | Racing | Team | Shooter | Space | Street | Football | Fighting | Truck | Role-Playing | Defense | Sports | Massively Multiplayer Online | Wargame | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||
| Afghanistan | 86.0 | 46.869565 | 68.352941 | 15.166667 | 17.818182 | 37.851852 | 27.176471 | 56.000000 | 23.837838 | 20.146341 | 24.888889 | 19.333333 | 32.666667 | 0.000000 | 0.000000 |
| Albania | 99.0 | 32.333333 | 32.333333 | 10.111111 | 9.000000 | 6.692308 | 15.666667 | 32.333333 | 7.333333 | 24.000000 | 6.692308 | 4.882353 | 7.333333 | 5.666667 | 3.761905 |
| Algeria | NaN | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| American Samoa | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Andorra | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Yemen | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Zambia | 92.0 | 25.333333 | 49.142857 | 30.095238 | 10.181818 | 14.222222 | 30.095238 | 106.285714 | 9.777778 | 13.052632 | 2.810811 | 4.903226 | 39.058824 | 4.903226 | 0.000000 |
| Zimbabwe | 93.0 | 43.000000 | 133.000000 | 13.000000 | 22.166667 | 7.893617 | 46.846154 | 80.500000 | 31.888889 | 56.636364 | 6.725490 | 0.000000 | 34.176471 | 0.000000 | 8.555556 |
| Åland Islands | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
250 rows × 15 columns
| 3D | Puzzle | Racing | Team | Shooter | Street | Football | Board Games | Kart | Role-Playing | Truck | Sports | Fighting | Space | Pet | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||
| Afghanistan | 94.0 | 60.666667 | 69.0 | 25.578947 | 29.294118 | 29.294118 | 94.000000 | 20.086957 | 0.000000 | 25.578947 | 11.647059 | 21.272727 | 22.571429 | 44.000000 | 7.636364 |
| Albania | NaN | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| Algeria | NaN | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| American Samoa | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Andorra | 88.0 | 73.714286 | 0.0 | 58.588235 | NaN | 25.500000 | 42.545455 | 13.531915 | 29.379310 | 40.173913 | 26.709677 | 15.906977 | 0.000000 | 21.333333 | 0.000000 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Yemen | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Zambia | 97.0 | 22.000000 | 47.0 | 24.272727 | 3.976744 | 20.076923 | 97.000000 | 6.375000 | 1.225352 | 2.882353 | 22.000000 | 34.500000 | 9.000000 | 5.823529 | 2.357143 |
| Zimbabwe | 94.0 | 48.545455 | 194.0 | 24.000000 | 22.571429 | 54.000000 | 114.000000 | 9.384615 | 3.677419 | 0.000000 | 114.000000 | 40.153846 | 21.272727 | 4.909091 | 0.000000 |
| Åland Islands | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
250 rows × 15 columns
| Puzzle | 3D | Team | Racing | Street | Football | Board Games | Shooter | Role-Playing | Truck | Sports | Music | Space | Fighting | Pet | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||
| Afghanistan | 85.0 | 121.363636 | 50.217391 | 85.000000 | 36.724138 | 135.000000 | 19.090909 | 47.500000 | 15.000000 | 42.692308 | 40.555556 | 42.692308 | 14.411765 | 33.387097 | 0.000000 |
| Albania | 98.0 | 198.000000 | 48.000000 | 98.000000 | 48.000000 | 198.000000 | 18.000000 | 23.000000 | 13.384615 | 64.666667 | 38.000000 | 23.000000 | 9.764706 | 16.181818 | 13.384615 |
| Algeria | 97.0 | inf | 72.000000 | 72.000000 | 147.000000 | 297.000000 | 9.500000 | 24.272727 | 17.000000 | 147.000000 | 20.076923 | 97.000000 | 22.000000 | 297.000000 | 17.000000 |
| American Samoa | 0.0 | 170.270270 | 0.000000 | 0.000000 | 127.272727 | 185.714286 | 0.000000 | NaN | 0.000000 | 0.000000 | 0.000000 | 170.270270 | 132.558140 | 0.000000 | 0.000000 |
| Andorra | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Yemen | 70.0 | 200.769231 | 85.384615 | 23.571429 | 55.714286 | 30.000000 | 0.000000 | 0.000000 | 66.774194 | 48.947368 | 0.000000 | 46.923077 | 32.500000 | 303.333333 | 15.454545 |
| Zambia | 71.0 | 212.666667 | 141.588235 | 178.142857 | 67.666667 | 293.222222 | 22.785714 | 27.862745 | 8.179487 | 109.095238 | 132.111111 | 937.666667 | 23.727273 | 38.441860 | 6.802469 |
| Zimbabwe | 87.0 | 87.000000 | 41.166667 | 247.000000 | 73.666667 | 172.714286 | 23.111111 | 22.135135 | 6.696970 | 247.000000 | 73.666667 | 105.181818 | 10.214286 | 27.625000 | 8.311475 |
| Åland Islands | 50.0 | 33.333333 | 85.135135 | 0.000000 | 0.000000 | 36.206897 | 44.339623 | 0.000000 | 0.000000 | 33.333333 | 0.000000 | 0.000000 | 37.719298 | 0.000000 | 0.000000 |
250 rows × 15 columns
| Puzzle | 3D | Team | Street | Board Games | Football | Racing | Shooter | Truck | Sports | Trainer | Role-Playing | Music | Space | Golf | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||
| Afghanistan | 82.0 | 145.636364 | 63.818182 | 63.818182 | 42.000000 | 110.571429 | 87.882353 | 22.909091 | 48.666667 | 21.130435 | 120.461538 | 36.545455 | 67.714286 | 42.000000 | 29.368421 |
| Albania | 97.0 | 72.000000 | 39.857143 | 39.857143 | 9.000000 | 147.000000 | 39.857143 | 24.272727 | 57.000000 | 39.857143 | 18.428571 | 9.500000 | 15.750000 | 12.000000 | 3.976744 |
| Algeria | 93.0 | 693.000000 | 93.000000 | 226.333333 | 23.434783 | 226.333333 | 93.000000 | 28.000000 | 226.333333 | 24.818182 | 80.500000 | 28.000000 | 133.000000 | 34.176471 | 23.434783 |
| American Samoa | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Andorra | 78.0 | 53.862069 | 39.111111 | 35.894737 | 35.894737 | 25.826087 | 0.000000 | 0.000000 | 40.857143 | 28.000000 | 24.808511 | 0.000000 | 0.000000 | 0.000000 | 20.307692 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Yemen | 70.0 | 184.285714 | 63.750000 | 60.909091 | 14.776119 | 12.857143 | 20.847458 | 19.180328 | 43.170732 | 36.666667 | 36.666667 | 41.428571 | 22.631579 | 14.776119 | 11.095890 |
| Zambia | 57.0 | 116.259259 | 195.888889 | 50.478261 | 13.578947 | 315.333333 | 143.956522 | 21.179104 | 129.000000 | 136.166667 | 14.333333 | 2.263158 | 1390.333333 | 21.179104 | 8.807229 |
| Zimbabwe | 92.0 | 92.000000 | 45.333333 | 64.727273 | 11.512195 | 392.000000 | 192.000000 | 32.000000 | 392.000000 | 106.285714 | 9.021277 | 4.307692 | 106.285714 | 9.021277 | 0.000000 |
| Åland Islands | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
250 rows × 15 columns
| Puzzle | Board Games | Football | 3D | Team | Street | Racing | Sports | Kart | Shooter | Music | Golf | Role-Playing | Space | Truck | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||
| Afghanistan | 75.0 | 37.500000 | 67.592593 | 131.250000 | 24.019608 | 46.428571 | 50.757576 | 61.206897 | 29.347826 | 37.500000 | 31.818182 | 13.461538 | 34.523810 | 40.789474 | 0.000000 |
| Albania | 92.0 | 24.000000 | 192.000000 | 92.000000 | 64.727273 | 72.000000 | 53.538462 | 49.142857 | 9.777778 | 36.444444 | 42.000000 | 0.000000 | 28.363636 | 30.095238 | 80.888889 |
| Algeria | 86.0 | 52.666667 | 336.000000 | 686.000000 | 161.000000 | 452.666667 | 186.000000 | 59.684211 | 63.777778 | 49.636364 | 219.333333 | 46.869565 | 36.000000 | 63.777778 | 452.666667 |
| American Samoa | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Andorra | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Yemen | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Zambia | 63.0 | 15.112676 | 374.111111 | 71.823529 | 123.869565 | 43.434783 | 117.166667 | 180.647059 | 0.000000 | 22.677419 | 1196.333333 | 11.051948 | 7.578313 | 16.623188 | 111.000000 |
| Zimbabwe | 88.0 | 14.666667 | 588.000000 | 73.714286 | 48.000000 | 68.000000 | 159.428571 | 228.000000 | 3.384615 | 36.000000 | 121.333333 | 6.750000 | 14.666667 | 18.769231 | 288.000000 |
| Åland Islands | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
250 rows × 15 columns
| Puzzle | Board Games | Football | Team | Street | 3D | Sports | Golf | Kart | Space | Music | Racing | Shooter | Pet | Role-Playing | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||
| Afghanistan | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Albania | 87.0 | 23.111111 | 247.000000 | 68.250000 | 63.470588 | 87.000000 | 73.666667 | 17.232558 | 24.142857 | 15.888889 | 35.148148 | 43.521739 | 19.500000 | 43.521739 | 30.333333 |
| Algeria | 90.0 | 42.631579 | 240.000000 | 115.000000 | 323.333333 | 490.000000 | 61.428571 | 40.000000 | 48.823529 | 56.666667 | 132.857143 | 101.111111 | 33.478261 | 30.000000 | 24.482759 |
| American Samoa | 57.0 | 0.000000 | 57.000000 | 73.216216 | 23.153846 | 28.666667 | 0.000000 | 17.563380 | 27.491803 | 0.000000 | 59.380952 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| Andorra | 25.0 | 72.058824 | 26.351351 | 40.384615 | 107.926829 | 75.000000 | 0.000000 | 63.888889 | 112.500000 | 33.695652 | 52.118644 | NaN | 0.000000 | 0.000000 | 63.888889 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Yemen | 88.0 | 22.285714 | 7.047619 | 16.571429 | 42.545455 | 88.000000 | 9.052632 | 22.285714 | 7.354839 | 21.333333 | 7.047619 | 15.906977 | 16.571429 | 0.000000 | 36.000000 |
| Zambia | 66.0 | 7.463415 | 532.666667 | 79.333333 | 55.473684 | 53.179487 | 249.333333 | 23.627119 | 2.956522 | 16.000000 | 1666.000000 | 120.545455 | 26.714286 | 3.777778 | 11.945946 |
| Zimbabwe | 80.0 | 22.553191 | 646.666667 | 54.074074 | 48.965517 | 60.000000 | 161.818182 | 6.666667 | 3.255814 | 15.714286 | 63.333333 | 133.846154 | 20.816327 | 0.000000 | 7.777778 |
| Åland Islands | 42.0 | 47.454545 | 0.000000 | 70.888889 | 0.000000 | 35.548387 | 21.452055 | 43.754386 | 0.000000 | 0.000000 | 22.555556 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
250 rows × 15 columns
| Puzzle | Board Games | Football | Team | 3D | Kart | Golf | Sports | Street | Music | Pet | Space | Role-Playing | Shooter | Racing | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||
| Afghanistan | 65.0 | 32.307692 | 39.468085 | 42.777778 | 37.916667 | 11.666667 | 12.297297 | 26.403509 | 35.000000 | 8.209877 | 12.297297 | 28.636364 | 22.377049 | 10.454545 | 18.846154 |
| Albania | 88.0 | 29.379310 | 121.333333 | 73.714286 | 80.307692 | 16.571429 | 32.444444 | 48.000000 | 51.157895 | 36.000000 | 25.500000 | 24.363636 | 26.709677 | 16.571429 | 15.272727 |
| Algeria | 91.0 | 47.250000 | 171.000000 | 91.000000 | 291.000000 | 66.000000 | 60.230769 | 55.285714 | 216.000000 | 81.000000 | 22.034483 | 47.250000 | 28.500000 | 31.909091 | 66.000000 |
| American Samoa | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Andorra | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Yemen | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Zambia | 66.0 | 17.515152 | 646.000000 | 53.179487 | 51.000000 | 6.963855 | 17.515152 | 451.714286 | 63.142857 | 3366.000000 | 6.000000 | 17.515152 | 7.463415 | 20.838710 | 102.000000 |
| Zimbabwe | 81.0 | 21.425532 | 456.000000 | 40.375000 | 40.375000 | 10.230769 | 19.000000 | 153.727273 | 35.285714 | 51.370370 | 9.358209 | 19.775510 | 4.750000 | 17.538462 | 92.764706 |
| Åland Islands | 52.0 | 0.000000 | 0.000000 | 72.000000 | 0.000000 | 36.210526 | 37.714286 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | NaN | 0.000000 | 0.000000 |
250 rows × 15 columns
| Puzzle | Board Games | Team | Football | 3D | Sports | Kart | Street | Space | Golf | Pet | Music | Role-Playing | Flight | Shooter | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||
| Afghanistan | 89.0 | 31.307692 | 41.380952 | 34.833333 | 57.750000 | 34.833333 | 8.642857 | 44.000000 | 57.750000 | 10.153846 | 7.032787 | 25.666667 | 25.666667 | 34.833333 | 25.666667 |
| Albania | 97.0 | 39.857143 | 47.000000 | 97.000000 | 97.000000 | 34.500000 | 12.000000 | 47.000000 | 24.272727 | 11.285714 | 47.000000 | 34.500000 | 15.750000 | 17.000000 | 15.750000 |
| Algeria | 90.0 | 61.428571 | 80.909091 | 156.666667 | 240.000000 | 73.333333 | 61.428571 | 190.000000 | 56.666667 | 33.478261 | 20.303030 | 61.428571 | 22.258065 | 66.923077 | 25.714286 |
| American Samoa | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Andorra | 0.0 | 0.000000 | 150.000000 | 0.000000 | 222.580645 | 40.845070 | 233.333333 | 72.413793 | 100.000000 | 88.679245 | 0.000000 | 0.000000 | 58.730159 | 0.000000 | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Yemen | 92.0 | 30.095238 | 45.333333 | 45.333333 | 152.000000 | 32.000000 | 25.333333 | 36.444444 | 8.666667 | 17.806452 | 13.052632 | 19.586207 | 22.769231 | 42.000000 | 10.181818 |
| Zambia | 66.0 | 21.737705 | 72.250000 | 816.000000 | 39.913043 | 227.538462 | 3.362637 | 39.913043 | 16.746269 | 12.575342 | 10.155844 | 1666.000000 | 6.476190 | 19.968254 | 23.627119 |
| Zimbabwe | 83.0 | 33.000000 | 28.945946 | 323.000000 | 45.962963 | 195.500000 | 0.000000 | 43.714286 | 23.476190 | 8.373134 | 5.666667 | 51.000000 | 0.000000 | 19.956522 | 31.571429 |
| Åland Islands | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
250 rows × 15 columns
| Puzzle | Board Games | Football | 3D | Team | Sports | Golf | Street | Defense | Pet | Kart | Space | Music | Horse Racing | Shooter | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||
| Afghanistan | 83.0 | 43.714286 | 48.384615 | 34.515152 | 43.714286 | 104.428571 | 13.909091 | 25.500000 | 10.868852 | 13.909091 | 15.692308 | 28.945946 | 18.416667 | 12.310345 | 18.416667 |
| Albania | 91.0 | 41.000000 | 103.500000 | 43.941176 | 38.368421 | 33.857143 | 18.272727 | 30.130435 | 41.000000 | 20.032258 | 11.000000 | 30.130435 | 19.125000 | 5.285714 | 12.428571 |
| Algeria | 93.0 | 63.000000 | 168.000000 | 226.333333 | 80.500000 | 93.000000 | 43.000000 | 226.333333 | 34.176471 | 24.818182 | 43.000000 | 51.333333 | 56.636364 | 14.212121 | 31.888889 |
| American Samoa | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Andorra | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Yemen | 88.0 | 63.000000 | 54.666667 | 73.714286 | 24.363636 | 58.588235 | 26.709677 | 18.000000 | 7.672131 | 17.268293 | 13.000000 | 22.285714 | 12.489796 | 17.268293 | 14.666667 |
| Zambia | 65.0 | 18.846154 | 840.000000 | 37.916667 | 124.090909 | 315.000000 | 11.052632 | 36.428571 | 7.682927 | 5.229885 | 4.772727 | 22.377049 | 1131.666667 | 3.888889 | 20.555556 |
| Zimbabwe | 79.0 | 26.727273 | 329.000000 | 20.176471 | 32.846154 | 189.000000 | 7.767123 | 21.000000 | 7.378378 | 4.301205 | 5.923077 | 15.206897 | 37.333333 | 54.000000 | 21.857143 |
| Åland Islands | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
250 rows × 15 columns
| Puzzle | Board Games | Team | Football | 3D | Sports | Street | Golf | Pet | Space | Kart | Music | Truck | Role-Playing | Defense | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||
| Afghanistan | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Albania | 84.0 | 37.333333 | 50.666667 | 78.117647 | 43.259259 | 43.259259 | 35.612903 | 20.363636 | 78.117647 | 26.105263 | 18.042553 | 39.172414 | 78.117647 | 27.243243 | 31.058824 |
| Algeria | 83.0 | 43.714286 | 96.333333 | 195.500000 | 195.500000 | 83.000000 | 195.500000 | 28.945946 | 30.222222 | 60.272727 | 51.000000 | 60.272727 | 225.857143 | 25.500000 | 34.515152 |
| American Samoa | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Andorra | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Yemen | 82.0 | 28.153846 | 28.153846 | 67.714286 | 132.000000 | 29.368421 | 30.648649 | 0.000000 | 0.000000 | 19.500000 | 7.352113 | 18.000000 | 44.068966 | 15.962264 | 14.142857 |
| Zambia | 73.0 | 12.130435 | 76.846154 | 648.000000 | 25.941176 | 310.500000 | 33.000000 | 18.762712 | 6.333333 | 16.548387 | 2.347826 | 648.000000 | 115.105263 | 4.034483 | 5.926829 |
| Zimbabwe | 80.0 | 16.363636 | 35.555556 | 313.333333 | 26.511628 | 161.818182 | 37.142857 | 12.786885 | 4.096386 | 14.482759 | 4.390244 | 46.666667 | 180.000000 | 3.809524 | 9.411765 |
| Åland Islands | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
250 rows × 15 columns
This dataframe was created using the interest over region graphs of google trends. Each dataframe is for a different year. The index columns shows the country each value was from. Each subsequent column shows the proportional mean amount of searches for the column name and country. This was done by comparing each value with a 'yardstick', another keyword, which was not a genre, and scaling each graph to allow the yardstick to be same through out. This dataframe was used to get the most searched genre for each country over the years.
for i in range(2014, 2023):
display(pd.read_csv('game' + str(i) + '.csv', index_col=0))
| Super Smash Bros. for Wii U | Dark Souls II | Out of the Park Baseball 15 | Dragon Age: Inquisition | forma.8 | The Binding of Isaac: Rebirth | Mario Kart 8 DLC Pack 1 | Diablo III: Reaper of Souls | Divinity: Original Sin | Dark Souls II: Crown of the Ivory King | ... | MX Vs ATV: Supercross | Gravity Badgers | Deus Ex: The Fall | One Piece: Romance Dawn | Wayward Manor | 4PM | SoulCalibur: Lost Swords | Rekoil | Sonic Boom: Rise of Lyric | Magus | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||||||||
| Afghanistan | NaN | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.0 | ... | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | NaN | 0.0 | 0.000000 |
| Albania | 0.0 | 354.545455 | 0.0 | 222.580645 | 88.679245 | 0.000000 | 0.0 | 108.333333 | 0.000000 | 0.0 | ... | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | NaN | 0.000000 |
| Algeria | 40.0 | 401.538462 | 0.0 | 162.222222 | 154.285714 | 13.170732 | 0.0 | 255.789474 | 22.191781 | 0.0 | ... | 0.0 | 0.0 | 29.552239 | 0.0 | 8.181818 | 0.0 | 0.0 | 0.0 | 0.0 | 11.428571 |
| American Samoa | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Andorra | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Yemen | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Zambia | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.0 | ... | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 |
| Zimbabwe | 0.0 | 0.000000 | 0.0 | 69.491525 | 0.000000 | NaN | 0.0 | 49.253731 | 194.117647 | 0.0 | ... | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 |
| Åland Islands | 0.0 | 0.000000 | 0.0 | 36.986301 | 0.000000 | 0.000000 | 0.0 | 222.580645 | 0.000000 | 0.0 | ... | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 |
250 rows × 232 columns
| The Witcher 3: Wild Hunt | Journey | Bloodborne | Mario Kart 8 DLC Pack 2 | The Witcher 3: Wild Hunt - Hearts of Stone | Pillars of Eternity | 3D Gunstar Heroes | Dark Souls II: Scholar of the First Sin | Nuclear Throne | Destiny: The Taken King | ... | Infinity Runner | Rodea the Sky Soldier | Devil's Third | Hatred | Enki | MX vs. ATV Supercross Encore | Chronus Arc | Tony Hawk's Pro Skater 5 | Zombeer | Afro Samurai 2: Revenge of Kuma Volume One | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||||||||
| Afghanistan | 73.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | NaN | 0.0 | 0.0 | 0.0 | 0.0 | ... | 0.0 | 0.0 | 0.0 | 0.000000 | NaN | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| Albania | 90.0 | 0.0 | 21.250000 | 0.0 | NaN | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | ... | NaN | 0.0 | NaN | 0.000000 | 5.151515 | 0.0 | 0.0 | NaN | 0.0 | 0.0 |
| Algeria | 94.0 | 0.0 | 6.244898 | 0.0 | 1.594937 | 5.764706 | 0.0 | 0.0 | 0.0 | 0.0 | ... | 0.0 | 0.0 | 0.0 | 0.593407 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| American Samoa | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Andorra | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | ... | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| Yemen | 70.0 | NaN | 90.000000 | 0.0 | 0.000000 | 0.000000 | 0.0 | NaN | 0.0 | 0.0 | ... | NaN | NaN | 0.0 | 0.000000 | 0.000000 | 0.0 | NaN | 0.0 | 0.0 | 0.0 |
| Zambia | 49.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | ... | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| Zimbabwe | 73.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | ... | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| Åland Islands | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
250 rows × 244 columns
| Out of the Park Baseball 17 | The Witcher 3: Wild Hunt - Blood and Wine | Forza Horizon 3: Hot Wheels | Stephen's Sausage Roll | NBA 2K17 | Dark Souls III: The Ringed City | Titanfall 2 | Battlefield 1 | World of Warcraft: Legion | The Witness | ... | Zenith (2016) | 7 Days to Die | The Huntsman: Winter's Curse | MilitAnt | Bombshell (2016) | Dead or Alive Xtreme 3: Fortune | Umbrella Corps | Crystal Rift | Ghostbusters | Dino Dini's Kick Off Revival | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||||||||
| Afghanistan | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.00000 | 108.333333 | 0.00000 | 150.000000 | 0.000000 | 0.000000 | ... | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 |
| Albania | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.00000 | 112.765957 | 0.00000 | 100.000000 | 26.582278 | 20.481928 | ... | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 38.888889 | 0.0 |
| Algeria | 0.0 | 78.571429 | 104.081633 | 0.0 | 29.87013 | 525.000000 | 29.87013 | 455.555556 | 138.095238 | 28.205128 | ... | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 20.481928 | 0.0 | 0.0 | 7.526882 | 0.0 |
| American Samoa | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Andorra | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.00000 | 0.000000 | 0.00000 | 0.000000 | 0.000000 | 0.000000 | ... | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 |
| Yemen | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Zambia | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.00000 | 0.000000 | 0.00000 | 0.000000 | 0.000000 | 0.000000 | ... | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 |
| Zimbabwe | 0.0 | 25.000000 | 0.000000 | 0.0 | 0.00000 | 0.000000 | 0.00000 | 0.000000 | 0.000000 | 0.000000 | ... | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 16.279070 | 0.0 |
| Åland Islands | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
250 rows × 282 columns
| Super Mario Odyssey | Divinity: Original Sin II | Persona 5 | Mario Kart 8 Deluxe | F1 2017 | Final Fantasy XIV: Stormblood | Rez Infinite | Horizon Zero Dawn | NieR: Automata | Nex Machina: Death Machine | ... | Moto Racer 4 | Inmates | Verdun | Reservoir Dogs: Bloody Days | Dead Alliance | Touhou Kobuto V: Burst Battle | Rugby 18 | Inner Chains | Dying: Reborn | Vroom in the Night Sky | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||||||||
| Afghanistan | 0.0 | NaN | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.00000 | 0.0 | ... | NaN | 0.0 | 0.000000 | 0.0 | NaN | NaN | 0.0 | 0.0 | 0.0 | 0.0 |
| Albania | 26.0 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.00000 | 0.0 | ... | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| Algeria | 48.0 | 9.176471 | 31.870968 | 17.333333 | 5.142857 | 0.0 | 0.0 | 56.333333 | 39.22807 | 0.0 | ... | 0.0 | 0.0 | 5.777778 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| American Samoa | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Andorra | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Yemen | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Zambia | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.00000 | 0.0 | ... | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| Zimbabwe | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.00000 | 0.0 | ... | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| Åland Islands | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
250 rows × 322 columns
| Undertale | Forza Horizon 4 | Bastion | Monster Hunter: World | Return of the Obra Dinn | Hyper Light Drifter | Ikaruga | Velocity 2X | Transistor | Destiny 2: Forsaken | ... | Tennis World Tour 2 | Bravo Team | KURSK | Gungrave VR | Hello Neighbor | Heavy Fire: Red Shadow | Underworld Ascendant | Fantasy Hero: Unsigned Legacy | Gene Rain | Wild West Online | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||||||||
| Afghanistan | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Albania | 58.0 | 0.000000 | 0.000000 | 74.666667 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | ... | 0.0 | 0.0 | 0.000000 | 0.0 | 60.439024 | 0.0 | 0.00000 | 0.0 | 0.0 | 0.0 |
| Algeria | 41.0 | 119.787879 | 29.059701 | 151.714286 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | ... | 0.0 | 0.0 | 10.411765 | 0.0 | 78.209302 | 0.0 | 12.95122 | 0.0 | 0.0 | 0.0 |
| American Samoa | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Andorra | 0.0 | 0.000000 | 0.000000 | NaN | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | ... | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.00000 | 0.0 | NaN | 0.0 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | 0.0 | 0.000000 | 0.000000 | 0.000000 | NaN | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | ... | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.00000 | 0.0 | 0.0 | 0.0 |
| Yemen | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Zambia | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | ... | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.00000 | 0.0 | 0.0 | 0.0 |
| Zimbabwe | 0.0 | 28.205128 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | ... | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.00000 | 0.0 | 0.0 | 0.0 |
| Åland Islands | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | ... | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.00000 | 0.0 | 0.0 | 0.0 |
250 rows × 305 columns
| Beat Saber | Final Fantasy XIV: Shadowbringers | Disco Elysium | Tetris Effect: Connected | F1 2019 | Asgard's Wrath | What Remains of Edith Finch | Baba Is You | Dragon Quest Builders 2 | MLB The Show 19 | ... | Wolfenstein: Cyberpilot | Modern Combat: Blackout | Decay of Logos | Monster Jam Steel Titans | Paranoia: Happiness is Mandatory | WWE 2K20 | Everreach: Project Eden | Dollhouse | Blades of Time | Eternity: The Last Unicorn | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||||||||
| Afghanistan | 0.0 | 0.0 | 0.0 | NaN | 0.000000 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | ... | 0.0 | 194.117647 | 0.0 | 0.0 | NaN | 0.000000 | 0.0 | 0.0 | NaN | 0.0 |
| Albania | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | ... | 0.0 | 88.679245 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 |
| Algeria | 22.0 | 0.0 | 0.0 | 0.0 | 15.975904 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | ... | 0.0 | 144.857143 | 0.0 | 0.0 | 0.0 | 28.849315 | 0.0 | 0.0 | 23.298701 | 0.0 |
| American Samoa | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Andorra | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | ... | 0.0 | NaN | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 |
| Yemen | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Zambia | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | ... | 0.0 | 17.647059 | 0.0 | 0.0 | 0.0 | 8.695652 | 0.0 | 0.0 | 0.000000 | 0.0 |
| Zimbabwe | 0.0 | NaN | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | ... | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 |
| Åland Islands | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | ... | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 |
250 rows × 244 columns
| Persona 5 Royal | Half-Life: Alyx | Demon's Souls | DOOM Eternal | Pistol Whip | Final Fantasy VII Remake Intergrade | Super Mega Baseball 3 | Grindstone | Monster Hunter: World - Iceborne | Persona 4 Golden | ... | Last Encounter | Star Horizon | Remothered: Broken Porcelain | The Dark Eye : Book of Heroes | Cooking Mama: Cookstar | Arc of Alchemist | The Elder Scrolls: Blades | Street Power Soccer | Tamarin | XIII (Remake) | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||||||||
| Afghanistan | 0.0 | 0.000000 | 0.000000 | 108.333333 | 0.0 | 150.000000 | 0.0 | 0.0 | 0.000000 | 0.0 | ... | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 |
| Albania | 33.0 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 72.583333 | 0.0 | 0.0 | 0.000000 | 0.0 | ... | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 |
| Algeria | 17.0 | 60.103448 | 13.511628 | 73.603774 | 0.0 | 213.428571 | 0.0 | 0.0 | 37.289855 | 0.0 | ... | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 9.222222 | 0.0 |
| American Samoa | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Andorra | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Yemen | 33.0 | NaN | 0.000000 | 0.000000 | 0.0 | 130.058824 | 0.0 | 0.0 | 0.000000 | 0.0 | ... | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 |
| Zambia | 0.0 | 0.000000 | 0.000000 | 8.695652 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 | ... | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 |
| Zimbabwe | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 33.333333 | 0.0 | 0.0 | 0.000000 | 0.0 | ... | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 |
| Åland Islands | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.0 | NaN | 0.0 | 0.0 | 0.000000 | 0.0 | ... | 0.0 | 0.0 | 0.0 | NaN | 0.0 | 0.0 | 0.0 | 0.0 | NaN | 0.0 |
250 rows × 255 columns
| Tetris Effect: Connected | Psychonauts 2 | Tony Hawk's Pro Skater 1 + 2 | Super Mario 3D World + Bowser's Fury | Synth Riders | DUSK | Ratchet & Clank: Rift Apart | Deathloop | Halo Infinite | Crash Bandicoot 4: It's About Time | ... | Tennis World Tour 2 | Date Night Bowling | TASOMACHI: Behind the Twilight | Elite: Dangerous - Odyssey | Apex Legends | AWAY: The Survival Series | Akiba's Trip: Hellbound & Debriefed | Balan Wonderworld | Of Bird and Cage | eFootball 2022 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||||||||
| Afghanistan | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 38.888889 | 0.00 | 0.000000 | 0.000000 | 0.000000 | ... | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 |
| Albania | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.00 | 0.000000 | 69.491525 | 0.000000 | ... | 0.0 | 0.0 | 0.0 | 0.0 | 156.410256 | 0.0 | 0.0 | 0.0 | 0.0 | 49.253731 |
| Algeria | 0.0 | 26.582278 | 0.0 | 72.413793 | 0.0 | 0.000000 | 56.25 | 38.888889 | 156.410256 | 78.571429 | ... | 0.0 | 0.0 | 0.0 | 0.0 | 177.777778 | 0.0 | 0.0 | 0.0 | 0.0 | 150.000000 |
| American Samoa | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Andorra | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Yemen | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | ... | 0.0 | 0.0 | 0.0 | 0.0 | 88.679245 | 0.0 | 0.0 | 0.0 | 0.0 | 51.515152 |
| Zambia | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | ... | 0.0 | 0.0 | 0.0 | 0.0 | 12.359551 | 0.0 | 0.0 | 0.0 | 0.0 | 23.456790 |
| Zimbabwe | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.00 | 0.000000 | 23.456790 | 0.000000 | ... | 0.0 | 0.0 | 0.0 | 0.0 | 9.890110 | 0.0 | 0.0 | 0.0 | 0.0 | 53.846154 |
| Åland Islands | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | ... | 0.0 | 0.0 | 0.0 | NaN | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 |
250 rows × 142 columns
| Elden Ring | The Stanley Parable: Ultra Deluxe | Rogue Legacy 2 | Xenoblade Chronicles 3 | Horizon Forbidden West | Monster Hunter Rise | Monster Hunter Rise.1 | Citizen Sleeper | Tunic | Kirby and the Forgotten Land | ... | Dynasty Warriors 9 Empires | The Ramp | Dusk Diver 2 | DOLMEN | Edge Of Eternity | Tower of Fantasy | Diablo Immortal | Matchpoint: Tennis Championships | The Waylanders | Babylon's Fall | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| geoName | |||||||||||||||||||||
| Afghanistan | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Albania | 62.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.000000 | 0.0 | ... | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 26.406780 | 0.0 | 0.0 | 0.0 |
| Algeria | 85.0 | 0.0 | 0.0 | 1.304348 | 6.428571 | 8.809524 | 8.809524 | 0.0 | 0.957447 | 0.0 | ... | 0.0 | 0.0 | 0.0 | 4.480519 | 0.0 | 9.590164 | 15.612245 | 0.0 | 0.0 | 0.0 |
| American Samoa | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.000000 | 0.0 | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Andorra | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Western Sahara | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.000000 | 0.0 | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| Yemen | 74.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.000000 | 0.0 | ... | NaN | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 |
| Zambia | 14.0 | 0.0 | 0.0 | 0.000000 | 2.659794 | 0.000000 | 0.000000 | 0.0 | 0.000000 | 0.0 | ... | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 |
| Zimbabwe | 22.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.000000 | 0.0 | ... | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 |
| Åland Islands | 44.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.000000 | 0.0 | ... | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.0 | NaN | 0.0 |
250 rows × 110 columns
This dataframe was created using the interest over region graphs of google trends. Each dataframe is for a different year. The index columns shows the country each value was from. Each subsequent column shows the proportional mean amount of searches for the column name and country. This was done by comparing each value with a 'yardstick', another keyword, which was not a game, and scaling each graph to allow the yardstick to be same through out. This dataframe was used to get the most searched game for each country over the years.
Most data cleaning was manually done for the game codes as some were faulty, due to the lack of consistency in google trends. There were also some wrong suggestions, that led to the incorrect code being recorded. As the faulty codes were random, but in my opinion were still useful, I manually went to google trends, out the faulty terms and chose the correct code. As some games were given codes when they did not even have one, their names were also sometimes put instead. The code for this will be in the appendix.
Likewise, for the merging of certain country names, to get the right country code, there had to be some manual cleaning of names again, so both had the same names for the merging. This code will be in the EDA. The rest of the cleaning is here, even though some was also manual.
df = pd.read_csv('metaScrape.csv', index_col=0)
df.iloc[df[df.name == 'God of War'].iloc[:2, 0].index, 0] = 'God of War (2018)' # This is to prevent two games with the same name from getting dropped, as they were different games
df = df.drop_duplicates(subset=['name'], ignore_index=True) # Removes all duplicate games, which were released in different platform, as recounting them will jumble up the google trends data
df = df[~(df['name'].str.contains('Edition'))]
df = df[~(df['name'].str.contains('Collection'))]
df = df[~(df['name'].str.contains('Remaster'))]
df = df[~(df['name'].str.contains('HD'))] # Removes any remasters, collections or editions as we only want to analyse new games
df['index'] = df.index
df3 = pd.read_csv('metaScrape4.csv')
df3 = df3[df3.sales.notnull()] # Removes null sales
df3 = df3.drop_duplicates(subset=['name'], keep='first') # Drops any duplicate games to preven double count
df3.sales = df3.sales.str.split('m').str[0].astype(float) # Convert sales to float
df3 = df3.drop(df3[df3.sales == 0].index) # Drop games with no sales, as the theses games are obscure games which were not in metacritic
df_genres = pd.read_csv('genres.csv')
df_genres.iloc[0, -1] = '/m/06c9r' # Corrects a code
df_genres.drop(df_genres.loc[df_genres['genre'] == '', 'index'], inplace=True) # Drops empty genres
df_genres.loc[df_genres.Code.isnull(), 'Code'] = df_genres.loc[df_genres.Code.isnull(), 'genre'] # Sets null code as the name
df_genres.drop(df_genres.loc[df_genres['genre'].isin(['Massively Multiplayer', 'Sim', 'Miscellaneous', 'Other', 'Soccer', 'Party / Minigame', 'Videos']), 'index'], inplace=True) # Removes genres which are sub genres, random, or already given before with a slightly different name
Firstly, we would like to format some of our dataframes to make some useful EDAs. We can do this by first applying a function to extract the genres from the list for each row
tqdm.pandas()
df = pd.read_csv('metaScrape3.csv', index_col=0) # Reading the csv which contains the webscrape data from dataset 1 and 1.1
dict1 = {'genre' : [], 'rating' : [], 'year' : []} # Defining a new dictionary, which will be converted to a dataframe
def getGenre(row): # Function which goes through all games and separates the genres which is a list
gameGenre = row.genre.split(',')
for i in gameGenre:
dict1['genre'].append(i)
dict1['rating'].append(row.rating)
dict1['year'].append(row.year)
df.apply(getGenre, axis=1)
df_genres = pd.DataFrame(dict1)
After defining the dataframe to make the graph, we will firstly see the count of genres for all the games, and also ensure that there are no duplicates. Due to the sheer amount of genres, I just want to analyse the top 15 genres with the most games. We would also define the proportion for each genre, to allow us to make the treemap.
genreCount = pd.DataFrame(df_genres[['genre']].value_counts(), columns=['Count']) # Counting the number of times a genre appeared
genres = pd.read_csv('genres.csv', index_col=0) # Reading the csv which contains the genres we would like to see, as some are just duplicates, with slightly different names
genreCount = pd.merge(genreCount, genres['genre'], on='genre', how='right') # Merging both so there are no duplicate genres
genreCount = genreCount.sort_values(by='Count', ascending=False)[:15] # As there are around 160 genres, we just want to analyse and compare the share of the top 15
genreCount['Proportion'] = (genreCount.Count / genreCount.Count.sum())*100 # Calculating proportion for treemap
Finally, after all the set up, let us make some graphs. Lets us visualise the graphs. I am making one bar plot to allow me to easily compare the number of games for each genre. We will also make a donut chart to compare the percentage share among the top most common genres
plt.figure(figsize=(25,5))
ax = sns.barplot(x ='genre', y='Count', data = genreCount, palette="viridis")
ax = ax.bar_label(ax.containers[0])
plt.title('Comparison between the number of games for each genre')
plt.ylabel('Number of games')
plt.xlabel('Genre')
plt.show()
px.pie(genreCount, values='Count', names='genre', hole=0.5, title="Comparison between the percentage of games for each genre")
As we can see, most games are under the Action genre, which has a 19.3% share amount the most common genres and has 4345 games. It has a very big leap comapred to second place which is Shooter with 9.6% and 2162 games. The change in games count for subsequent genres is realtively minute.
Let us compare with the most searches genres. yearlygenre.csv include the genres which have the most interest over the entire year, for each year from 2004 to 2022. From this data, we would like to see the genres that appeared the most, with a maximum of 1 per year.
dfyear = pd.read_csv('yearlygenre.csv', index_col=0)
dfCount = pd.DataFrame(dfyear.genre.value_counts()).reset_index().iloc[:15]
dfCount.columns = ['genre', 'numYear']
plt.figure(figsize=(30,10))
sns.barplot(dfCount, y='numYear', x='genre')
plt.title('Comparison of the number of years a genre was in the top 15 seached genres of the year')
plt.ylabel('Number of Years')
plt.xlabel('Genre')
plt.show()
dfCount.merge(genreCount, on='genre', how='inner')
| genre | numYear | Count | Proportion | |
|---|---|---|---|---|
| 0 | Puzzle | 19 | 1089 | 4.837420 |
| 1 | 3D | 19 | 1204 | 5.348259 |
| 2 | Role-Playing | 18 | 1475 | 6.552061 |
| 3 | Shooter | 14 | 2162 | 9.603767 |
There is a overlap of 4 games only, with all of them having high number of years where they were part of the top 15 genres with the most interest. Firstly, puzzle video games are very popular especially for casual audiences, which are a larger demographic than hard core video gamers. Many popular puzzle games include Candy Crush, Tetris, etc. Due to the rise in technology, most games are also 3D, with certain retro or indie games which are 2D. With how many gamers play mainstream games, it makes sense that 3D is a popular and common genre. Role-playing and shooters are few of the most widespread genres which have a range of acclaimed games such as Cyberpunk and Valorant, so it makes sense that they are also the most searched. They may also be subjectted to controversy, possibly increasing the amount of searches regarding them.
Firstly, we will read the original scraped data and some manipulation to it to see the platform with the most games per year.
platforms = pd.read_csv('metaScrape.csv', index_col=0)
# This is basically to only get the top platform. This is done by first getting the count of the games and sorting by it, and then dropping any duplicate years. This will ensure only the highest count stays the same
platsort = platforms.groupby(['year','data'])['name'].count().reset_index()
platsort = platsort.sort_values(by='name',ascending=False)
platsort = platsort.drop_duplicates(subset=['year'],keep='first').sort_values(by='year', ascending=False)
f, ax = plt.subplots(figsize=(6, 15))
sns.set_color_codes("pastel")
platsort['yearStr'] = platsort.year.astype(str) # For the barplot to regonise what the labels are, we need to convert it to string
fig = sns.barplot(x="name", y="yearStr", data=platsort, color="r")
for i, p in enumerate(zip(platsort.data, platsort['name'])): # This is to label each column with the platform name and the number of games for it
plt.text(s=(str(p[0]) + ' : ' + str(p[1])),x=10,y=i,fontweight='bold',color='white')
plt.title('Comparison between the number of games released by the top platform of the year')
plt.xlabel('Number of games')
plt.ylabel('Year')
plt.show()
There are many years where a certain console overshadowed PC and other consoles. These consoles were seen normally the most famous during its time, such as the PlayStation 2 in 2002. This could have led more developers to make games for this console, and thus pad the number of games for that console.
There is an overall increasing trend, except for dips in certain years. 2006, 2012, 2014 and 2019 had a dip for the number of games. I think this is due to a new generation of consoles releasing the next year, or was already released. This may have caused developers to spend more time with the new console tech. The dip for 2022 is mainly due to the fact that this data is until Aug 2022. PC has the most games in the early 2010s and 2000s due to the switch in console generation, but recently, due to many console exclusives being also released on PCs has caused them to be the platform with the most games recently.
plt.figure(figsize=(40, 7))
platCount = platforms.groupby('data')[['name']].count().reset_index().sort_values(by='name',ascending=False)
ax = sns.barplot(x ='data', y='name', data = platCount, palette="viridis")
ax = ax.bar_label(ax.containers[0])
plt.title('Comparison between the number of games released for each platform')
plt.ylabel('Number of Games')
plt.xlabel('Platform')
Text(0.5, 0, 'Platform')
PC as a platform has the most number of games, by a mile, with 5087, double of the second place PS4. The top 4 runner ups were all once the platform with the most games in a year, thus it makes sense they are the closest runner ups. There are what looks like stepped pattern in the decrease of the number of games. The platform with the least games was Stadia, which was unsupported due to being clound only, and also the lack of any games from a first party games studio. The last 3 platfroms, before Stadia, all were at the end of their life, and only had gams for 2 years for N64 and DreamCast and 4 years for the PS1. The inverse is true for the PS5 and Xbox Series X, with both launching very recently and only have 3 years of games.
dict1 = {'genre' : [], 'rating' : [], 'year' : [], 'platform' : []}
def getGenre(row):
gameGenre = row.genre.split(',')
for i in gameGenre:
dict1['genre'].append(i)
dict1['rating'].append(row.rating)
dict1['year'].append(row.year)
dict1['platform'].append(row.data)
platforms = platforms.drop('month', axis=1)
platforms = platforms.merge(df.loc[:, ['name', 'genre', 'rating']], on='name', how='left').dropna()
platforms.progress_apply(getGenre, axis=1)
df_plat = pd.DataFrame(dict1)
0%| | 0/18692 [00:00<?, ?it/s]
Over here, we reuse the function to extract the genre, but now for dataframe platforms. However, we need the genre and rating too, so we will merge it first with the earlier dataframe to get the rating and genre associated with the games.
Now using this, let us make some heatmaps.
plt.figure(figsize=(8,8))
df_plat = df_plat[df_plat['genre'].isin(genreCount.genre)] # We are only displaying the genres with the most games, this will thus allow us to have more datapoints
dfHeat = df_plat.groupby(['platform','genre'])['rating'].median().reset_index()
dfHeat = dfHeat.pivot('platform','genre','rating')
sns.heatmap(dfHeat, cmap='turbo')
plt.title('Median rating by platform and genre')
plt.xlabel('Genre')
plt.ylabel('Platform')
Text(50.99999999999999, 0.5, 'Platform')
There are many missing genres for some platform. One trend is that many recent platforms such as Xbox Series X, Stadia, Switch and PlayStation 5 do not have the genres of Fantasy, Modern and Sci-Fi. A game in a modern setting is not novel anymore, so this could lead to developers not thinking that their game would be under such a genre. For the other 2, they are mainly time consuming games to make, with the scale of the games and also due to creating new lore. Stadia, which is a largely unsupported platform due to being new and having a cloud nature, has a low amount of genres. The missing genres for the Nintendo 64 and PlayStation 1 was due to the low amount of games released for both platforms.
For 2D games, the the DreamCast has two of the most highest median rating, one for First-Person and one for 2D. Xbox Series X however has the highest overall median rating for all genres. The rating from most of the other genres and platforms are in the 65 to 77 range, with some being less and more. The lowest was for Adventure in the DreamCast. The PlayStation has the highest number of low rating genres with 5 while the PlayStation 5 has the highest number of high rating genres with 9 games.
The genre with the most low ratings is Adventure with while the genre with the most high ratings is 2D.
plt.figure(figsize=(8,8))
dfHeat = df_plat.groupby(['platform','year'])['rating'].median().reset_index()
dfHeat = dfHeat.pivot('platform','year','rating')
sns.heatmap(dfHeat,cmap='magma')
plt.title('Median rating by platform and year')
plt.xlabel('Year')
plt.ylabel('Platform')
Text(50.99999999999999, 0.5, 'Platform')
There is a trend where for plenty of platforms (3DS, DS, DreamCast, GBA, N64, PS2, PS4, Wii U, Xbox One) where the last year of the platforms life has the highest median rating compared to the other years. Some also have the opposite trend, such as Stadia and PS1, where their last year had a significant drop in rating compared to the previous years. Over the years, the rating for many platforms seem to increase, however some do not have a clear trend, such as GBA, PS1, PS2, PS3. The highest median rating is for the Wii U in 2017 whereas the lowest is the PS1 in 2003. The platform with the shortest years of games were Stadia, DreamCast and N64. The platform with the longest years of games released was the PC with 23 while the console with the longest years of games was the PS2 with 11.
plt.figure(figsize=(8,8))
mean = df_genres[df_genres['genre'].isin(genreCount.genre)]
dfHeat = mean.groupby(['year','genre'])['rating'].median().reset_index()
dfHeat = dfHeat.pivot('year','genre','rating')
sns.heatmap(dfHeat,cmap='viridis')
plt.title('Median rating by year and genre')
plt.xlabel('Genre')
plt.ylabel('Year')
Text(51.0, 0.5, 'Year')
The missing of any games from the Fantasy, Mordern and Sci-Fi could explain why they were missing for the PS5, and Xbox Series X. Another thing about these genres is that the last few years where they were released had really low ratings, for Fantasy in 2019, for Modern in 2017 and for Sci-Fi in 2019. For many genres, it seems that their highest ratings were at the start of the 2000s, leading to a plateu in ratings, with some variation for multiple uears, until recently where the ratings increased again. This could be due to a lower amount of games made from 2000 to 2004. Recently, the increase could be due to geeting the median of games released before September, as a result causing us to miss some low rated games. I however also think that the qualitly controls of game selling platforms have also increased, however there could still be some poor rated games being made.
sales = pd.read_csv('sales.csv')
fig = go.Figure(data=go.Violin(y=sales["sales"], box_visible=True, line_color='black',
meanline_visible=True, fillcolor='lightseagreen', opacity=0.6,
x0='Sales / 10e6'))
fig.update_layout(
title_text="Violinplot of sales",
)
fig.update_layout(yaxis_zeroline=False) # Removes the y-axis zeroline
fig.show()
The distributuon is skewed to the right and it is unimodal. The median sales is 0.28 10e6, while the mean sales is 1.26 10e6. The range is 237.99 10e6 while the IQR is 0.89 10e6. There are a lot of outliers that skews the range and mean severly. All of the outliers have much more the the uppper whisker.
Let us now look when games are released
list1 = []
dict1 = {'Jan' : 1, 'Feb' : 2, 'Mar' : 3, 'Apr' : 4, 'May' : 5, 'Jun' : 6, 'Jul' : 7, 'Aug' : 8, 'Sep' : 9, 'Oct' : 10, 'Nov' : 11, 'Dec' : 12} # This has to be done as to_datetime uses int
def month(row):
list1.append(dict1[row.month])
df.progress_apply(month, axis=1)
df['num'] = list1
df['date_formatted'] = pd.to_datetime( # Converts month and year to a datetime object, specifying date will be too specific
dict(
year=df['year'],
month=df['num'],
day=1
))
df['year_formatted'] = pd.to_datetime( # Converts year to datetime object
dict(
year=df['year'],
month=1,
day=1
))
datedf = df.groupby('date_formatted')[['name']].count().reset_index()
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# Create figure
fig = go.Figure()
fig.add_trace(
go.Scatter(x=list(datedf.date_formatted), y=list(datedf.name), name='Games per month')) # Makes a lineplot for
# Sets title
fig.update_layout(
title_text="Timeseries of number of games released",
yaxis_title='Number of games',
xaxis_title='Date'
)
# Adds a range slider
fig.update_layout(
xaxis=dict(
rangeselector=dict(
buttons=list([
dict(count=6,
label="6m",
step="month",
stepmode="backward"),
dict(count=1,
label="YTD",
step="year",
stepmode="todate"),
dict(count=1,
label="1y",
step="year",
stepmode="backward"),
dict(step="all")
])
),
rangeslider=dict(
visible=True
),
type="date"
)
)
fig.show()
pd.plotting.autocorrelation_plot(datedf.name)
<AxesSubplot: xlabel='Lag', ylabel='Autocorrelation'>
We can see from this autocorrelation graph that our data is periodic, and repeats every 12 months. So let us smoothen that out
# Create figure
fig = go.Figure()
fig.add_trace(
go.Scatter(x=list(datedf.date_formatted), y=signal.savgol_filter(list(datedf.name), 12, 2), name='Smoothened games per month')) # Makes a lineplot for
# Sets title
fig.update_layout(
title_text="Timeseries of number of games released",
yaxis_title='Number of games',
xaxis_title='Date'
)
# Adds a range slider
fig.update_layout(
xaxis=dict(
rangeselector=dict(
buttons=list([
dict(count=6,
label="6m",
step="month",
stepmode="backward"),
dict(count=1,
label="YTD",
step="year",
stepmode="todate"),
dict(count=1,
label="1y",
step="year",
stepmode="backward"),
dict(step="all")
])
),
rangeslider=dict(
visible=True
),
type="date"
)
)
fig.show()
We can see a upside down parabola shape from the April of one year to the April of another, with it repeating again and again until 2010, with March being the least for 2008. We can safely say that April from these years had the lowest. The maximum for this parabola was generally October or November, with it being other months as the humps became less pronounced.
list1 = []
def month(row):
list1.append(dict1[row.month])
sales.apply(month, axis=1)
sales['num'] = list1
sales['date_formatted'] = pd.to_datetime(
dict(
year=sales['year'],
month=sales['num'],
day=1
)
)
salesdf = sales.groupby('date_formatted')[['sales']].median().reset_index()
salesdf.sales = salesdf.sales * 10e6
# Add traces
list2 = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']
px.line(x=list2, y=sales.groupby('num')[['sales']].median().sales)
fig.update_layout(
title_text= "Trend of games sales"
)
fig.update_xaxes(title_text="Months")
# Set y-axes titles
fig.update_yaxes(title_text="Sales / 10e6")
fig.show()
px.line(x=list2, y=sales.groupby('num')[['sales']].count().sales)
# Add figure title
fig.update_layout(
title_text= "Trend of number of games released"
)
# Set x-axis title
fig.update_xaxes(title_text="Months")
# Set y-axes titles
fig.update_yaxes(title_text="Number of games")
fig.show()
There are large hump for both graphs from September to November. This could be due to the the holiday season of Novemeber and Decmeber, which generally have a lot of holidays (Christmas, Thanksgiving). There is also an increase of sales in May, but no increase in games released. This increase in sales could be due to the summer holidays in certain countries, however developers may prioritise the winter holidays more. There is a drop in games sales and number of games released in July, January and December.
plt.figure(figsize=(12,8))
sns.pointplot(data=sales.groupby('day')[['sales']].median(), y="sales", x=sales.groupby('day')[['sales']].median().index)
plt.title('Median of sales over day')
plt.xlabel('Day')
plt.ylabel('Median of Sales/10e6')
plt.plot()
[]
There are multiple instances in the graph of an increased, followed by a decreased and so on. In fact this trend is reprodruced multiple times. This could be as since after a game releases in one country first, the subsequent days will see releases in other countries, as a result, it could be possible that developers do not want to release during the hype of another game
# Create figure
fig = go.Figure()
fig.add_trace(
go.Scatter(x=list(salesdf.date_formatted), y=list(salesdf.sales)))
# Set title
fig.update_layout(
title_text="Time series with range slider and selectors"
)
# Add range slider
fig.update_layout(
xaxis=dict(
rangeselector=dict(
buttons=list([
dict(count=6,
label="6m",
step="month",
stepmode="backward"),
dict(count=1,
label="YTD",
step="year",
stepmode="todate"),
dict(count=1,
label="1y",
step="year",
stepmode="backward"),
dict(step="all")
])
),
rangeslider=dict(
visible=True
),
type="date"
)
)
fig.show()
The sales of games has increased severly recently, with Jan 2022, having the highest sales of 110 million. There are however other spikes over the years as well. THe lowest sales in month was Aug 2005 with 770K.
fig = go.Figure(data=go.Violin(y=df["rating"], box_visible=True, line_color='black',
meanline_visible=True, fillcolor='lightseagreen', opacity=0.6,
x0='Rating'))
fig.update_layout(yaxis_zeroline=False, title_text='Violin plot of game ratings')
fig.show()
plt.figure(figsize=(10,10))
df['rating'].hist(edgecolor='black')
plt.title('Histogram of rating')
plt.ylabel('Number of games')
plt.xlabel('Rating')
plt.show()
# ax = plt.axvline(df['rating'].median(),color='r',linestyle='dashed')
# plt.annotate('Median: ' + str(df['rating'].median()), xy=(32, 72), xytext=(53, 3500), fontsize=15)
The distributuon is skewed to the left and it is unimodal, with the mode in the histogram being the 72 to 80 bin.. The median rating is 72, while the mean sales is 70. The range is 87 while the IQR is 13. There are a lot of outliers that skews the range severly. All of the outliers have much less rating than the the lower whisker in the violin plot.
nrow=3
ncol=5
genres = genreCount.genre
fig = plt.figure(figsize=(16,8))
gs = fig.add_gridspec(nrow, ncol)
axes = gs.subplots(sharex=True, sharey=True)
df_list = []
for i in genres:
df_list.append(df_genres.loc[df_genres.genre == i,'rating'])
sns.set_color_codes("bright")
for count in range(nrow * ncol):
nrow, ncol = divmod(count, 3)
df_list[count].hist(edgecolor='black', alpha=0.3, color='red', ax=axes[ncol, nrow])
axes[ncol, nrow].text(30, 750, str(genres.iloc[count]))
axes[ncol, nrow].axvline(df['rating'].median(),color='b',linestyle='dashed') # This shows the median of all game ratings
axes[ncol, nrow].axvline(df_list[count].median(),color='g',linestyle='dashed') # This shows the median of the ratings for the games of these genres
plt.suptitle("Rating distribution across genres")
plt.show()
The median rating of all the genres are very close to the median rating of all games. However, some genres have slightly higher ratings, which are Role-Playing, Platformer, Strategy and 2D (which has the highest median rating). Some also have lower ratings, which are Action, Shooter, 3D (which has the lowest median rating), Arcade and Modern.
nrow=5
ncol=4
years = df.year.unique()
fig = plt.figure(figsize=(16,8))
gs = fig.add_gridspec(nrow, ncol)
axes = gs.subplots(sharex=True, sharey=True)
df_list = []
for i in years:
df_list.append(df_genres.loc[df_genres.year == i,'rating'])
for count in range(nrow * ncol):
nrow, ncol = divmod(count, 5)
df_list[count].hist(edgecolor='black', alpha=0.3, color='red', ax=axes[ncol, nrow])
axes[ncol, nrow].text(30, 500, str(years[count]))
axes[ncol, nrow].axvline(df['rating'].median(),color='b',linestyle='dashed') # This shows the median of all game ratings
axes[ncol, nrow].axvline(df_list[count].median(),color='g',linestyle='dashed') # This shows the median of the ratings of games from the year
plt.suptitle("Rating distribution across years")
plt.show()
The median rating of all the years are very close to the median rating of all games, however, there are larger changes then genre. 2022 has a much higher median rating than the median, while 2007 has the least. There is also another trend where from 2017 to 2022, the median rating for the year was higher than the median rating of all games. However, from 2005 to 2011, the median rating was lower than the median rating of all games
years = dfyear.year.unique()
df_list = []
for i in years:
df_list.append(dfyear.loc[dfyear.year == i,['genre', 'Searches']])
fig = make_subplots(
rows=3, cols=6,
specs = [[{"type": "pie"},{"type": "pie"}, {"type": "pie"}, {"type": "pie"}, {"type": "pie"}, {"type": "pie"}],
[{"type": "pie"},{"type": "pie"}, {"type": "pie"}, {"type": "pie"}, {"type": "pie"}, {"type": "pie"}],
[{"type": "pie"},{"type": "pie"}, {"type": "pie"}, {"type": "pie"}, {"type": "pie"}, {"type": "pie"}]],
subplot_titles=years[:18].astype(str))
for i in range(1, 4):
for j in range(1, 7):
fig.add_trace(go.Pie(values=dfyear.loc[dfyear.year == years[(i-1) * 6 + j - 1], 'Searches'].iloc[:5], labels=dfyear.loc[dfyear.year == years[(i-1) * 6 + j - 1], 'genre'].iloc[:5]),
row=i, col=j)
fig.update_layout(height=700, width=1150, showlegend=True, title_text='Percentage among top 5 most searched genre each year')
fig.show()
Puzzle has the highest perentage accross all the years, except for 2014 to 2010, where 3D games had the highest percentage of searches. It was also the only genre in all the years. From 2022 to 2017, board games had the second highest percentage. Role-playing was second from 2007 to 2005.
dfnew = pd.DataFrame()
dict1 = {'Country' : [], 'Genre' : []}
def maximus(row):
dict1['Country'].append(row.geoName)
dict1['Genre'].append(row.iloc[1:].astype(float).idxmax())
for i in range(2004, 2023):
dict1 = {'Country' : [], 'Genre' : []}
dftemp = pd.read_csv('genrecountry' + str(i) + '.csv').dropna()
dftemp.apply(maximus, axis=1)
dftemp = pd.DataFrame(dict1)
dftemp['Year'] = i
dfnew = pd.concat([dfnew, dftemp])
# Cleaning of the names to allow us to merge and get the country codes
dfnew.loc[dfnew.Country == 'Antigua & Barbuda', 'Country'] = 'Antigua and Barbuda'
dfnew.loc[dfnew.Country == 'Bolivia', 'Country'] = 'Bolivia (Plurinational State of)'
dfnew.loc[dfnew.Country == 'Faroe Islands', 'Country'] = 'Faroe Islands (the)'
dfnew.loc[dfnew.Country == 'Netherlands', 'Country'] = 'Netherlands (the)'
dfnew.loc[dfnew.Country == 'Bahamas', 'Country'] = 'Bahamas (the)'
dfnew.loc[dfnew.Country == 'Bosnia & Herzegovina', 'Country'] = 'Bosnia and Herzegovina'
dfnew.loc[dfnew.Country == 'Trinidad & Tobago', 'Country'] = 'Trinidad and Tobago'
dfnew.loc[dfnew.Country == 'St. Vincent & Grenadines', 'Country'] = 'Saint Vincent and the Grenadines'
dfnew.loc[dfnew.Country == 'British Virgin Islands', 'Country'] = 'Virgin Islands (British)'
dfnew.loc[dfnew.Country == 'U.S. Virgin Islands', 'Country'] = 'Virgin Islands (U.S.)'
dfnew.loc[dfnew.Country == 'Vietnam', 'Country'] = 'Viet Nam'
dfnew.loc[dfnew.Country == 'Venezuela', 'Country'] = 'Venezuela (Bolivarian Republic of)'
dfnew.loc[dfnew.Country == 'United States', 'Country'] = 'United States of America (the)'
dfnew.loc[dfnew.Country == 'United Kingdom', 'Country'] = 'United Kingdom of Great Britain and Northern Ireland (the)'
dfnew.loc[dfnew.Country == 'United Arab Emirates', 'Country'] = 'United Arab Emirates (the)'
dfnew.loc[dfnew.Country == 'Turks & Caicos Islands', 'Country'] = 'Turks and Caicos Islands (the)'
dfnew.loc[dfnew.Country == 'Tanzania', 'Country'] = 'Tanzania, United Republic of'
dfnew.loc[dfnew.Country == 'Taiwan', 'Country'] = 'Taiwan (Province of China)'
dfnew.loc[dfnew.Country == 'Sudan', 'Country'] = 'Sudan (the)'
dfnew.loc[dfnew.Country == 'Sint Maarten', 'Country'] = 'Sint Maarten (Dutch part)'
dfnew.loc[dfnew.Country == 'St. Lucia', 'Country'] = 'Saint Lucia'
dfnew.loc[dfnew.Country == 'St. Kitts & Nevis', 'Country'] = 'Saint Kitts and Nevis'
dfnew.loc[dfnew.Country == 'St. Helena', 'Country'] = 'Saint Helena, Ascension and Tristan da Cunha'
dfnew.loc[dfnew.Country == 'St. Barthélemy', 'Country'] = 'Saint Barthélemy'
dfnew.loc[dfnew.Country == 'Russia', 'Country'] = 'Russian Federation (the)'
dfnew.loc[dfnew.Country == 'Philippines', 'Country'] = 'Philippines (the)'
dfnew.loc[dfnew.Country == 'Palestine', 'Country'] = 'Palestine, State of'
dfnew.loc[dfnew.Country == 'Northern Mariana Islands', 'Country'] = 'Northern Mariana Islands (the)'
dfnew.loc[dfnew.Country == 'Niger', 'Country'] = 'Niger (the)'
dfnew.loc[dfnew.Country == 'Moldova', 'Country'] = 'Moldova (the Republic of)'
dfnew.loc[dfnew.Country == 'Marshall Islands', 'Country'] = 'Marshall Islands (the)'
dfnew.loc[dfnew.Country == 'North Macedonia', 'Country'] = 'Republic of North Macedonia'
dfnew.loc[dfnew.Country == 'Laos', 'Country'] = 'Lao People\'s Democratic Republic (the)'
dfnew.loc[dfnew.Country == 'South Korea', 'Country'] = 'Korea (the Republic of)'
dfnew.loc[dfnew.Country == 'Iran', 'Country'] = 'Iran (Islamic Republic of)'
dfnew.loc[dfnew.Country == 'Gambia', 'Country'] = 'Gambia (the)'
dfnew.loc[dfnew.Country == 'Falkland Islands (Islas Malvinas)', 'Country'] = 'Falkland Islands (the) [Malvinas]'
dfnew.loc[dfnew.Country == 'Dominican Republic', 'Country'] = 'Dominican Republic (the)'
dfnew.loc[dfnew.Country == 'Cook Islands', 'Country'] = 'Cook Islands (the)'
dfnew.loc[dfnew.Country == 'Congo - Kinshasa', 'Country'] = 'Congo (the Democratic Republic of the)'
dfnew.loc[dfnew.Country == 'Congo - Brazzaville', 'Country'] = 'Congo (the)'
dfnew.loc[dfnew.Country == 'Cayman Islands', 'Country'] = 'Cayman Islands (the)'
country = pd.read_csv("CountryCodesThreeLetter.csv", index_col=0)
country = country.dropna()
dfnew2 = dfnew.merge(country, on='Country', how='inner')
dfnew2.Year = dfnew2.Year.astype(int)
dfnew2 = dfnew2.sort_values(by='Year')
dfnew3 = dfnew2
fig = px.choropleth(dfnew3,
locations="Alpha-3 code",
featureidkey='properties.ADMIN',
color='Genre',
hover_name='Country',
animation_frame='Year',
color_discrete_sequence=px.colors.qualitative.Light24
)
fig.update_layout(width=1000, height=800)
fig.show()
The highest searched genres for each country has changed rapidly over time and has been volatile.
k = dfnew.groupby('Genre')[['Country']].count().sort_values(by='Country', ascending=False)[:15]
dfnews = dfnew.groupby(['Genre', 'Year'])[['Country']].count().loc[k.index]
years = dfnew.Year.unique()
d = {'Genre' : [], 'Year' : [], 'Count' : []}
for i in k.index:
for j in years:
try:
d['Genre'].append(i)
d['Year'].append(j)
d['Count'].append(dfnews.loc[i].loc[j].iloc[-1])
except KeyError:
d['Count'].append(0)
df3 = pd.DataFrame(d)
fig = px.bar(df3, x='Genre', y="Count", color="Genre",
animation_frame="Year", animation_group="Genre", range_y=[0, 60], color_discrete_sequence=px.colors.qualitative.Light24)
fig.show()
Puzzle had the highest countries where it was first with 55 in 2020. Over time, its searched has increased. 3D peaked in 2014 with 50 countries where it was first. Football peaked in 2018 with 36 countries.
dfnew = pd.DataFrame()
dict1 = {'Country' : [], 'Game' : []}
def maximus(row):
dict1['Country'].append(row.geoName)
dict1['Game'].append(row.iloc[1:].astype(float).idxmax())
for i in range(2014, 2023):
dict1 = {'Country' : [], 'Game' : []}
dftemp = pd.read_csv('game' + str(i) + '.csv').dropna()
dftemp.apply(maximus, axis=1)
dftemp = pd.DataFrame(dict1)
dftemp['Year'] = i
dfnew = pd.concat([dfnew, dftemp])
dfnew.loc[dfnew.Country == 'Antigua & Barbuda', 'Country'] = 'Antigua and Barbuda'
dfnew.loc[dfnew.Country == 'Bolivia', 'Country'] = 'Bolivia (Plurinational State of)'
dfnew.loc[dfnew.Country == 'Faroe Islands', 'Country'] = 'Faroe Islands (the)'
dfnew.loc[dfnew.Country == 'Netherlands', 'Country'] = 'Netherlands (the)'
dfnew.loc[dfnew.Country == 'Bahamas', 'Country'] = 'Bahamas (the)'
dfnew.loc[dfnew.Country == 'Bosnia & Herzegovina', 'Country'] = 'Bosnia and Herzegovina'
dfnew.loc[dfnew.Country == 'Trinidad & Tobago', 'Country'] = 'Trinidad and Tobago'
dfnew.loc[dfnew.Country == 'St. Vincent & Grenadines', 'Country'] = 'Saint Vincent and the Grenadines'
dfnew.loc[dfnew.Country == 'British Virgin Islands', 'Country'] = 'Virgin Islands (British)'
dfnew.loc[dfnew.Country == 'U.S. Virgin Islands', 'Country'] = 'Virgin Islands (U.S.)'
dfnew.loc[dfnew.Country == 'Vietnam', 'Country'] = 'Viet Nam'
dfnew.loc[dfnew.Country == 'Venezuela', 'Country'] = 'Venezuela (Bolivarian Republic of)'
dfnew.loc[dfnew.Country == 'United States', 'Country'] = 'United States of America (the)'
dfnew.loc[dfnew.Country == 'United Kingdom', 'Country'] = 'United Kingdom of Great Britain and Northern Ireland (the)'
dfnew.loc[dfnew.Country == 'United Arab Emirates', 'Country'] = 'United Arab Emirates (the)'
dfnew.loc[dfnew.Country == 'Turks & Caicos Islands', 'Country'] = 'Turks and Caicos Islands (the)'
dfnew.loc[dfnew.Country == 'Tanzania', 'Country'] = 'Tanzania, United Republic of'
dfnew.loc[dfnew.Country == 'Taiwan', 'Country'] = 'Taiwan (Province of China)'
dfnew.loc[dfnew.Country == 'Sudan', 'Country'] = 'Sudan (the)'
dfnew.loc[dfnew.Country == 'Sint Maarten', 'Country'] = 'Sint Maarten (Dutch part)'
dfnew.loc[dfnew.Country == 'St. Lucia', 'Country'] = 'Saint Lucia'
dfnew.loc[dfnew.Country == 'St. Kitts & Nevis', 'Country'] = 'Saint Kitts and Nevis'
dfnew.loc[dfnew.Country == 'St. Helena', 'Country'] = 'Saint Helena, Ascension and Tristan da Cunha'
dfnew.loc[dfnew.Country == 'St. Barthélemy', 'Country'] = 'Saint Barthélemy'
dfnew.loc[dfnew.Country == 'Russia', 'Country'] = 'Russian Federation (the)'
dfnew.loc[dfnew.Country == 'Philippines', 'Country'] = 'Philippines (the)'
dfnew.loc[dfnew.Country == 'Palestine', 'Country'] = 'Palestine, State of'
dfnew.loc[dfnew.Country == 'Northern Mariana Islands', 'Country'] = 'Northern Mariana Islands (the)'
dfnew.loc[dfnew.Country == 'Niger', 'Country'] = 'Niger (the)'
dfnew.loc[dfnew.Country == 'Moldova', 'Country'] = 'Moldova (the Republic of)'
dfnew.loc[dfnew.Country == 'Marshall Islands', 'Country'] = 'Marshall Islands (the)'
dfnew.loc[dfnew.Country == 'North Macedonia', 'Country'] = 'Republic of North Macedonia'
dfnew.loc[dfnew.Country == 'Laos', 'Country'] = 'Lao People\'s Democratic Republic (the)'
dfnew.loc[dfnew.Country == 'South Korea', 'Country'] = 'Korea (the Republic of)'
dfnew.loc[dfnew.Country == 'Iran', 'Country'] = 'Iran (Islamic Republic of)'
dfnew.loc[dfnew.Country == 'Gambia', 'Country'] = 'Gambia (the)'
dfnew.loc[dfnew.Country == 'Falkland Islands (Islas Malvinas)', 'Country'] = 'Falkland Islands (the) [Malvinas]'
dfnew.loc[dfnew.Country == 'Dominican Republic', 'Country'] = 'Dominican Republic (the)'
dfnew.loc[dfnew.Country == 'Cook Islands', 'Country'] = 'Cook Islands (the)'
dfnew.loc[dfnew.Country == 'Congo - Kinshasa', 'Country'] = 'Congo (the Democratic Republic of the)'
dfnew.loc[dfnew.Country == 'Congo - Brazzaville', 'Country'] = 'Congo (the)'
dfnew.loc[dfnew.Country == 'Cayman Islands', 'Country'] = 'Cayman Islands (the)'
country = pd.read_csv("CountryCodesThreeLetter.csv", index_col=0)
country = country.dropna()
dfnew2 = dfnew.merge(country, on='Country', how='inner')
dfnew2.Year = dfnew2.Year.astype(int)
dfnew2 = dfnew2.sort_values(by='Year')
fig = px.choropleth(dfnew2,
locations="Alpha-3 code",
featureidkey='properties.ADMIN',
color='Game',
hover_name='Country',
animation_frame='Year',
color_discrete_sequence=px.colors.qualitative.Light24
)
fig.update_layout(width=1000, height=800)
fig.show()
plt.figure(figsize=(25,5))
ax = sns.barplot(x ='genre', y='Count', data = genreCount, palette="turbo")
ax = ax.bar_label(ax.containers[0])
plt.title('Comparison between the number of games for each genre')
plt.ylabel('Number of games')
plt.xlabel('Genre')
plt.annotate('', xy=(5, 2000), xytext=(1, 4000), arrowprops=dict(facecolor='red'))
plt.annotate('Slow decrease in number of game', xy=(1, 2000), xytext=(2, 3100), rotation=-18)
plt.show()
As we can see, most games are under the Action genre, which has 4345 games. It has a very big leap compared to second place which is Shooter with 2162 games. The change in games count for subsequent genres is realtively minute. This shows that apart from the first 2 genres, the amount of games released but the other genres is relatively uniform. However, another suprising thing is that the top 3 genres are action based (Action Adventure is a completely different genre compared to Action), which could be due to the popularity of these genres, due to the quick dopamine rush one can get from these games.
Let us compare with the most searches genres. yearlygenre.csv include the genres which have the most interest over the entire year, for each year from 2004 to 2022. From this data, we would like to see the genres that appeared the most, with a maximum of 1 per year.
dfyear = pd.read_csv('yearlygenre.csv', index_col=0)
dfCount = pd.DataFrame(dfyear.genre.value_counts()).reset_index().iloc[:15]
dfCount.columns = ['genre', 'numYear']
fig = px.bar(dfCount, y='numYear', x='genre', title='Comparison of the number of years a genre was in the top 15 seached genres of the year').update_layout(
yaxis_title="Number of Years", xaxis_title="Genre"
)
dfCount.merge(genreCount, on='genre', how='inner')
| genre | numYear | Count | Proportion | |
|---|---|---|---|---|
| 0 | Puzzle | 19 | 1089 | 4.837420 |
| 1 | 3D | 19 | 1204 | 5.348259 |
| 2 | Role-Playing | 18 | 1475 | 6.552061 |
| 3 | Shooter | 14 | 2162 | 9.603767 |
There is a overlap of 4 games only, with all of them having high number of years where they were part of the top 15 genres with the most interest. Firstly, puzzle video games are very popular especially for casual audiences, which are a larger demographic than hard core video gamers. Many popular puzzle games include Candy Crush, Tetris, etc. Due to the rise in technology, most games are also 3D, with certain retro or indie games which are 2D. With how many gamers play mainstream games, it makes sense that 3D is a popular and common genre. Role-playing and shooters are few of the most widespread genres which have a range of acclaimed games such as Cyberpunk and Valorant, so it makes sense that they are also the most searched. They may also be subjectted to controversy, possibly increasing the amount of searches regarding them.
plt.figure(figsize=(40, 7))
platCount = platforms.groupby('data')[['name']].count().reset_index().sort_values(by='name',ascending=False)
ax = sns.barplot(x ='data', y='name', data = platCount, palette="turbo")
ax = ax.bar_label(ax.containers[0])
plt.title('Comparison between the number of games released for each platform')
plt.ylabel('Number of Games')
plt.xlabel('Platform')
plt.annotate('', xy=(5, 2000), xytext=(1, 4000), arrowprops=dict(facecolor='red'))
plt.annotate('Large decline from PC onwards', xy=(1, 2000), xytext=(2, 3100), rotation=-20)
plt.show()
PC as a platform has the most number of games, by a mile, with 5087, double of the second place PS4. The top 4 runner ups were all once the platform with the most games in a year, thus it makes sense they are the closest runner ups. There are what looks like stepped pattern in the decrease of the number of games. The platform with the least games was Stadia, which was unsupported due to being clound only, and also the lack of any games from a first party games studio. The last 3 platfroms, before Stadia, all were at the end of their life, and only had gams for 2 years for N64 and DreamCast and 4 years for the PS1. The inverse is true for the PS5 and Xbox Series X, with both launching very recently and only have 3 years of games.
Over here, we reuse the function to extract the genre, but now for dataframe platforms. However, we need the genre and rating too, so we will merge it first with the earlier dataframe to get the rating and genre associated with the games.
Now using this, let us make some heatmaps.
plt.figure(figsize=(17,17))
df_plat = df_plat[df_plat['genre'].isin(genreCount.genre)] # We are only displaying the genres with the most games, this will thus allow us to have more datapoints
dfHeat = df_plat.groupby(['platform','genre'])['rating'].median().reset_index()
dfHeat = dfHeat.pivot('platform','genre','rating')
sns.heatmap(dfHeat,annot=True,cmap='turbo',linewidths=0.4)
plt.title('Median rating by platform and genre')
plt.xlabel('Genre')
plt.ylabel('Platform')
Text(132.0, 0.5, 'Platform')
There are many missing genres for some platform. One trend is that many recent platforms such as Xbox Series X, Stadia, Switch and PlayStation 5 do not have the genres of Fantasy, Modern and Sci-Fi. A game in a modern setting is not novel anymore, so this could lead to developers not thinking that their game would be under such a genre. For the other 2, they are mainly time consuming games to make, with the scale of the games and also due to creating new lore. Stadia, which is a largely unsupported platform due to being new and having a cloud nature, has a low amount of genres. The missing genres for the Nintendo 64 and PlayStation 1 was due to the low amount of games released for both platforms.
For 2D games, the the DreamCast has two of the most highest median rating, one for First-Person, 92, and one for 2D, 84,. Xbox Series X however has the highest overall median rating for all genres, a 97 for Puzzle. The rating from most of the other genres and platforms are in the 65 to 77 range, with some being less and more. The lowest was a 54 for Adventure in the DreamCast. The PlayStation has the highest number of low rating genres (Less than 65) with 5 while the PlayStation 5 has the highest number of high rating genres (More than 77) with 9 games.
The genre with the most low ratings (Less than 65) is Adventure with 6 while the genre with the most high ratings (More than 77) is 2D with 9.
plt.figure(figsize=(17,17))
dfHeat = df_plat.groupby(['platform','year'])['rating'].median().reset_index()
dfHeat = dfHeat.pivot('platform','year','rating')
sns.heatmap(dfHeat,annot=True,cmap='turbo',linewidths=0.4)
plt.title('Median rating by platform and year')
plt.xlabel('Year')
plt.ylabel('Platform')
Text(132.0, 0.5, 'Platform')
There is a trend where for plenty of platforms (3DS, DS, DreamCast, GBA, N64, PS2, PS4, Wii U, Xbox One) where the last year of the platforms life has the highest median rating compared to the other years. Some also have the opposite trend, such as Stadia and PS1, where their last year had a significant drop in rating compared to the previous years. Over the years, the rating for many platforms seem to increase, however some do not have a clear trend, such as GBA, PS1, PS2, PS3. The highest median rating is for the Wii U in 2017 whereas the lowest is the PS1 in 2003. The platform with the shortest years of games were Stadia, DreamCast and N64. The platform with the longest years of games released was the PC with 23 while the console with the longest years of games was the PS2 with 11.
The highest median rating was for the Wii in 2017 with a 97, while the lowest median rating was the PS1 in 2003, with a 25. The most common ratings fall in the range of 70 to 80, which was much higher than the one of platforms and genres.
# Create figure
fig = go.Figure()
fig.add_trace(
go.Scatter(x=list(datedf.date_formatted), y=signal.savgol_filter(list(datedf.name), 12, 2), name='Smoothened games per month')) # Makes a lineplot for
# Sets title
fig.update_layout(
title_text="Timeseries of number of games released",
yaxis_title='Number of games',
xaxis_title='Date'
)
# Adds a range slider
fig.update_layout(
xaxis=dict(
rangeselector=dict(
buttons=list([
dict(count=6,
label="6m",
step="month",
stepmode="backward"),
dict(count=1,
label="YTD",
step="year",
stepmode="todate"),
dict(count=1,
label="1y",
step="year",
stepmode="backward"),
dict(step="all")
])
),
rangeslider=dict(
visible=True
),
type="date"
)
)
fig.show()
We can see a upside down parabola shape from the April of one year to the April of another, with it repeating again and again until 2010, with March being the least for 2008. We can safely say that April from these years had the lowest. The maximum for this parabola was generally October or November, with it being other months as the humps became less pronounced.
fig = make_subplots(specs=[[{"secondary_y": True}]])
# Add traces
fig.add_trace(
go.Scatter(x=list2, y=sales.groupby('num')[['sales']].median().sales, name="Median sales of Games"),
secondary_y=False,
)
fig.add_trace(
go.Scatter(x=list2, y=sales.groupby('num')[['sales']].count().sales, name="Number of Games released"),
secondary_y=True,
)
# Add figure title
fig.update_layout(
title_text= "Trend of games sales vs number of games released"
)
# Set x-axis title
fig.update_xaxes(title_text="Months")
# Set y-axes titles
fig.update_yaxes(title_text="Sales / 10e6", secondary_y=False)
fig.update_yaxes(title_text="Number of games", secondary_y=True)
fig.show()
There are large hump for both graphs from September to November. This could be due to the the holiday season of Novemeber and Decmeber, which generally have a lot of holidays (Christmas, Thanksgiving). There is also an increase of sales in May, but no increase in games released. This increase in sales could be due to the summer holidays in certain countries, however developers may prioritise the winter holidays more. There is a drop in games sales and number of games released in July, January and December. This could be due to games being sold out, for the sales. For January and December, it makes sense not to release games as it would be too late to be in the Game Awards, or will be a distant memory when the next Game Awards come.
plt.figure(figsize=(10,10))
df['rating'].hist(edgecolor='black')
plt.title('Histogram of rating')
plt.ylabel('Number of games')
plt.xlabel('Rating')
ax = plt.axvline(df['rating'].median(),color='r',linestyle='dashed')
plt.annotate('Median: ' + str(df['rating'].median()), xy=(32, 72), xytext=(53, 3500), fontsize=15)
plt.show()
nrow=3
ncol=5
genres = genreCount.genre
fig = plt.figure(figsize=(16,8))
gs = fig.add_gridspec(nrow, ncol)
axes = gs.subplots(sharex=True, sharey=True)
df_list = []
for i in genres:
df_list.append(df_genres.loc[df_genres.genre == i,'rating'])
sns.set_color_codes("bright")
for count in range(nrow * ncol):
nrow, ncol = divmod(count, 3)
df_list[count].hist(edgecolor='black', alpha=0.3, color='red', ax=axes[ncol, nrow])
axes[ncol, nrow].text(30, 750, str(genres.iloc[count]))
axes[ncol, nrow].axvline(df['rating'].median(),color='b',linestyle='dashed') # This shows the median of all game ratings
axes[ncol, nrow].axvline(df_list[count].median(),color='g',linestyle='dashed') # This shows the median of the ratings for the games of these genres
plt.suptitle("Rating distribution across genres\nGreen line is the median rating of genre, Blue line is overall median rating")
plt.show()
The median rating of all the genres are very close to the median rating of all games. However, some genres have slightly higher ratings, which are Role-Playing, Platformer, Strategy and 2D (which has the highest median rating). Some also have lower ratings, which are Action, Shooter, 3D (which has the lowest median rating), Arcade and Modern.
nrow=5
ncol=4
years = df.year.unique()
fig = plt.figure(figsize=(16,8))
gs = fig.add_gridspec(nrow, ncol)
axes = gs.subplots(sharex=True, sharey=True)
df_list = []
for i in years:
df_list.append(df_genres.loc[df_genres.year == i,'rating'])
for count in range(nrow * ncol):
nrow, ncol = divmod(count, 5)
df_list[count].hist(edgecolor='black', alpha=0.3, color='red', ax=axes[ncol, nrow])
axes[ncol, nrow].text(30, 500, str(years[count]))
axes[ncol, nrow].axvline(df['rating'].median(),color='b',linestyle='dashed') # This shows the median of all game ratings
axes[ncol, nrow].axvline(df_list[count].median(),color='g',linestyle='dashed') # This shows the median of the ratings of games from the year
plt.suptitle("Rating distribution across years\nGreen line is the median rating of genre, Blue line is overall median rating")
plt.show()
The median rating of all the years are very close to the median rating of all games, however, there are larger changes then genre. 2022 has a much higher median rating than the median, while 2007 has the least. There is also another trend where from 2017 to 2022, the median rating for the year was higher than the median rating of all games. However, from 2005 to 2011, the median rating was lower than the median rating of all games
years = dfyear.year.unique()
df_list = []
for i in years:
df_list.append(dfyear.loc[dfyear.year == i,['genre', 'Searches']])
fig = make_subplots(
rows=3, cols=6,
specs = [[{"type": "pie"},{"type": "pie"}, {"type": "pie"}, {"type": "pie"}, {"type": "pie"}, {"type": "pie"}],
[{"type": "pie"},{"type": "pie"}, {"type": "pie"}, {"type": "pie"}, {"type": "pie"}, {"type": "pie"}],
[{"type": "pie"},{"type": "pie"}, {"type": "pie"}, {"type": "pie"}, {"type": "pie"}, {"type": "pie"}]],
subplot_titles=years[:18].astype(str))
for i in range(1, 4):
for j in range(1, 7):
fig.add_trace(go.Pie(values=dfyear.loc[dfyear.year == years[(i-1) * 6 + j - 1], 'Searches'].iloc[:5], labels=dfyear.loc[dfyear.year == years[(i-1) * 6 + j - 1], 'genre'].iloc[:5]),
row=i, col=j)
fig.update_layout(height=700, width=1150, showlegend=True, title_text='Percentage among top 5 most searched genre each year')
fig.update_traces(textinfo='none')
fig.show()
Puzzle has the highest perentage accross all the years, except for 2014 to 2010, where 3D games had the highest percentage of searches. It was also the only genre in all the years. From 2022 to 2017, board games had the second highest percentage. Role-playing was second from 2007 to 2005. Board games was second from 2017 to 2022. The highest percentage was 38.8% for Puzzle in 2020. The lowest percentage was 11.8% for 3D in 2020.
fig = px.choropleth(dfnew3,
locations="Alpha-3 code",
featureidkey='properties.ADMIN',
color='Genre',
hover_name='Country',
animation_frame='Year',
color_discrete_sequence=px.colors.qualitative.Light24
)
fig.update_layout(width=1000, height=800)
fig.show()
The highest searched genres for each country has changed rapidly over time and has been volatile. However, puzzle has been consistently the highest searched genre in Australia and the United States. 3D has also been consistent over the years, but it varies in which country it is in
dfnew2.loc[((dfnew2.Year == 2015) & (dfnew2.Game == 'Fallout 4: Automatron')), 'Game'] = 'Fallout 4'
fig = px.choropleth(dfnew2,
locations="Alpha-3 code",
featureidkey='properties.ADMIN',
color='Game',
hover_name='Country',
animation_frame='Year',
color_discrete_sequence=px.colors.qualitative.Light24
)
fig.update_layout(width=1000, height=800)
fig.show()
For each year, there was a stand out game which dominates all the country. For 2014, it was World of Warcraft: Warlords of Draenor. For 2015, the most searched Fallout 4, while its DLC its the breakout game of 2016. For 2017, the game with the highest reach was The Elder Scrolls V: Skyrim and 2018 it was Fortnite. FIFA 20 was the breakout game in 2019. Call of Duty: Warzone was the game with the highest country where is was the most searched. Call of Duty: Vanguard was the stand out game in 2021, and finally Elden ring in 2022.
For improvements, I would use another source other than Google Trends for search data because of it not having id codes for all games and genres, leading to less accuracy in the search data. I would either use another tool in addition with Google Trends, or use the other tool only. I would also like to find another way to get the searches specified for Console and PC games, and not mobile games, which are also include for the interest in genres.
For further work, I hope to extend this project by looking at more stats and seeing how they could be correleated, such as the developer of the game, the amount of players playing the game in a certain week, sales price and whether it is a GOTY awards winner.
This is the cleaning
df = pd.read_csv('cleaningMeta2.csv',index_col=0)
df.loc[df.name == '.hack//G.U. Last Recode', 'Code'] = '/g/11g8txr50k'
df.loc[df.name == 'Famicom Detective Club: The Missing Heir', 'Code'] = 'Famicom Detective Club: The Missing Heir'
df.loc[df.name == 'Hextech Mayhem: A League of Legends Story', 'Code'] = 'Hextech Mayhem: A League of Legends Story'
df.loc[df.name == 'Darksiders Genesis', 'Code'] = '/m/011l5s9c'
df.loc[df.name == 'Pokemon Sword / Shield: The Crown Tundra', 'Code'] = '/g/11jrgdnfk8'
df.loc[df.name == 'void tRrLM(); //Void Terrarium', 'Code'] = 'void tRrLM(); //Void Terrarium'
df.loc[df.name == 'Pokemon Sword / Shield: The Isle of Armor', 'Code'] = '/g/11k6f9p9dc'
df.loc[df.name == 'Resident Evil: Resistance', 'Code'] = '/g/11hdvdpwm3'
df.loc[df.name == 'Infini', 'Code'] = 'Infini'
df.loc[df.name == 'Final Fantasy VII', 'Code'] = '/m/0dvzv'
df.loc[df.name == 'Pokemon Sword / Shield Dual Pack', 'Code'] = '/g/11fk16tpkz'
df.loc[df.name == 'FIFA 20', 'Code'] = '/g/11hyd49rk6'
df.loc[df.name == 'Fate/Extella Link', 'Code'] = '/g/11fk0wkvgs'
df.loc[df.name == 'Devil May Cry', 'Code'] = '/m/031_55'
df.loc[df.name == "Marvel's Spider-Man", 'Code'] = '/g/11bzx4tgt5'
df.loc[df.name == "Dragon Quest Builders", 'Code'] = '/g/11b807hz5j'
df.loc[df.name == "Crash Bandicoot N. Sane Trilogy", 'Code'] = '/g/11c1ldfl8b'
df.loc[df.name == "Life is Strange 2", 'Code'] = 'Life is Strange 2'
df.loc[df.name == "Luigi's Mansion", 'Code'] = '/g/1q64lm9r5'
df.loc[df.name == "Tour de France 2018", 'Code'] = 'Tour de France 2018'
df.loc[df.name == "Hollow", 'Code'] = 'Hollow'
df.loc[df.name == "Forza Horizon 3: Hot Wheels", 'Code'] = '/g/11bzs55v4g'
df.loc[df.name == "Monster Hunter Stories", 'Code'] = '/g/11f006gvtd'
df.loc[df.name == "The Elder Scrolls Online: Morrowind", 'Code'] = '/g/11dfpjqlr4'
df.loc[df.name == "LEGO Marvel Super Heroes 2", 'Code'] = '/g/11dd_sgr0t'
df.loc[df.name == "Disney/Pixar Cars 3: Driven to Win", 'Code'] = '/g/11dfj4rps3'
df.loc[df.name == "Fate/Extella: The Umbral Star", 'Code'] = '/g/11c438hg8h'
df.loc[df.name == "Rush: A Disney / Pixar Adventure", 'Code'] = '/m/0kz2xtj'
df.loc[df.name == "Total War: WARHAMMER", 'Code'] = '/g/11bycc23kh'
df.loc[df.name == "DiRT Rally", 'Code'] = '/m/0134z8m5'
df.loc[df.name == "Ratchet & Clank", 'Code'] = '/m/010wb8qx'
df.loc[df.name == "Unravel", 'Code'] = 'Unravel'
df.loc[df.name == "Battlefleet Gothic: Armada", 'Code'] = '/m/012npm6w'
df.loc[df.name == "Valley", 'Code'] = 'Valley'
df.loc[df.name == "Transport Fever", 'Code'] = '/g/11c5m3m5t6'
df.loc[df.name == "Bridge Constructor", 'Code'] = '/g/11c67whk2l'
df.loc[df.name == "Tron RUN/r", 'Code'] = '/g/11bzq2_5tx'
df.loc[df.name == "Life is Strange", 'Code'] = '/g/0129c4zc'
df.loc[df.name == "Hand of Fate", 'Code'] = '/m/0134jnqz'
df.loc[df.name == "Inazuma Eleven Go: Chrono Stones: Wildfire", 'Code'] = 'Inazuma Eleven Go: Chrono Stones: Wildfire'
df.loc[df.name == "Star Wars Battlefront", 'Code'] = '/m/05b10f9'
df.loc[df.name == "Dying Light", 'Code'] = '/m/0vpvzzc'
df.loc[df.name == "The Evil Within: The Consequence", 'Code'] = 'The Evil Within: The Consequence'
df.loc[df.name == "Mercenaries Saga 2: Order Of The Silver Eagle", 'Code'] = 'Mercenaries Saga 2: Order Of The Silver Eagle'
df.loc[df.name == "Divinity: Original Sin", 'Code'] = '/m/0j_3rsw'
df.loc[df.name == "Super Mega Baseball", 'Code'] = '/m/013679bm'
df.loc[df.name == "Frozen Synapse Prime", 'Code'] = '/m/013679bm'
df.loc[df.name == "Call of Duty: Advanced Warfare", 'Code'] = '/m/010gp6bl'
df.loc[df.name == "Marvel Heroes 2015", 'Code'] = 'Marvel Heroes 2015'
df.loc[df.name == "The Evil Within", 'Code'] = 'The Evil Within'
df.loc[df.name == "Azure Striker Gunvolt", 'Code'] = '/g/1q620sbxf'
df.loc[df.name == "Surge Deluxe", 'Code'] = 'Surge Deluxe'
df.loc[df.name == "Risk of Rain", 'Code'] = '/m/0_frnxs'
df.loc[df.name == "The Denpa Men 2: Beyond the Waves", 'Code'] = 'The Denpa Men 2: Beyond the Waves'
df.loc[df.name == "Call of Duty: Black Ops II", 'Code'] = '/m/6u0ddg1nk'
df.loc[df.name == "Shelter", 'Code'] = 'Shelter'
df.loc[df.name == "Dynasty Warriors 8", 'Code'] = '/m/0nbv0r9'
df.loc[df.name == "Picross e3", 'Code'] = 'Picross e3'
df.loc[df.name == "Dynasty Warriors 7 Empires", 'Code'] = '/g/11cn68sl0q'
df.loc[df.name == "Legend of Dungeon", 'Code'] = 'Legend of Dungeon'
df.loc[df.name == "Senran Kagura Burst", 'Code'] = '/g/119x73_3j'
df.loc[df.name == "Pac-Man and the Ghostly Adventures", 'Code'] = '/m/010fhj63'
df.loc[df.name == "Horizon", 'Code'] = 'Horizon 4X'
df.loc[df.name == "Marvel Heroes", 'Code'] = 'Marvel Heroes'
df.loc[df.name == "Sniper: Ghost Warrior 2", 'Code'] = '/m/0gx1s3k'
df.loc[df.name == "Marvel Heroes", 'Code'] = 'Marvel Heroes'
df.loc[df.name == "Farming Simulator", 'Code'] = '/g/11cny30n9v'
df.loc[df.name == "FIFA Soccer 13", 'Code'] = '/m/0kyqzxz'
df.loc[df.name == "Forza Horizon", 'Code'] = '/m/0j674jh'
df.loc[df.name == "New Super Mario Bros. U", 'Code'] = '/m/0gwygtq'
df.loc[df.name == "Crusader Kings II", 'Code'] = '/m/0gx2sw9'
df.loc[df.name == "SoulCalibur V", 'Code'] = '/m/0gtvxhq'
df.loc[df.name == "NCAA Football 13", 'Code'] = '/m/0j3gdc1'
df.loc[df.name == "Retro/Grade", 'Code'] = 'Retro/Grade'
df.loc[df.name == "Marvel Pinball 3D", 'Code'] = 'Marvel Pinball 3D'
df.loc[df.name == "Zumba Fitness Rush", 'Code'] = 'Zumba Fitness Rush'
df.loc[df.name == "Ninja Gaiden Sigma Plus", 'Code'] = 'Ninja Gaiden Sigma Plus'
df.loc[df.name == "Disney/Pixar Brave", 'Code'] = '/m/0j62gsp'
df.loc[df.name == "One Piece: Pirate Warriors", 'Code'] = 'One Piece Pirate Warriors'
df.loc[df.name == "Disney Epic Mickey: The Power of Illusion", 'Code'] = '/m/0j7kknc'
df.loc[df.name == "Realms of Ancient War", 'Code'] = 'Realms of Ancient War'
df.loc[df.name == "Dark Souls", 'Code'] = 'Dark Souls'
df.loc[df.name == "Unity of Command", 'Code'] = '/m/0kz2ggb'
df.loc[df.name == "Orcs Must Die!", 'Code'] = '/m/0gjblh5'
df.loc[df.name == "Madden NFL 12", 'Code'] = 'Madden NFL 12'
df.loc[df.name == "Call of Duty: Black Ops - Annihilation", 'Code'] = '/m/0bwm8y4'
df.loc[df.name == "FIFA Soccer 11", 'Code'] = 'FIFA 11'
df.loc[df.name == "Split/Second", 'Code'] = '/m/05p7dd3'
df.loc[df.name == "Madden NFL 11", 'Code'] = 'Madden NFL 11'
df.loc[df.name == "Dance Central", 'Code'] = '/m/0c3vh7y'
df.loc[df.name == "Disney/Pixar Toy Story 3", 'Code'] = '/m/0bbxrf3'
df.loc[df.name == "Art Academy", 'Code'] = 'Art Academy'
df.loc[df.name == "Dark Fall 3: Lost Souls", 'Code'] = 'Dark Fall 3: Lost Souls'
df.loc[df.name == "Kinect Sports", 'Code'] = '/m/0cc7732'
df.loc[df.name == "MotoGP 09/10", 'Code'] = '/m/0kyr263'
df.loc[df.name == "Sackboy's Prehistoric Moves", 'Code'] = "Sackboy's Prehistoric Moves"
df.loc[df.name == "Blood Drive", 'Code'] = 'Blood Drive'
df.loc[df.name == "Tom Clancy's Ghost Recon", 'Code'] = '/m/012blkpq'
df.loc[df.name == "Starpoint Gemini", 'Code'] = '/m/09rwr8z'
df.loc[df.name == "Football Manager 2010", 'Code'] = 'Football Manager 2010'
df.loc[df.name == "LocoRoco 2", 'Code'] = '/m/04y5lw2'
df.loc[df.name == "ZEN Pinball", 'Code'] = '/m/0102g27c'
df.loc[df.name == "The Path", 'Code'] = 'The Path'
df.loc[df.name == "Wings of Prey", 'Code'] = 'Wings of Prey'
df.loc[df.name == "Grand Slam Tennis", 'Code'] = 'Grand Slam Tennis'
df.loc[df.name == "ArmA II", 'Code'] = '/m/02r2br8'
df.loc[df.name == "Resident Evil Archives: Resident Evil", 'Code'] = '/g/120x6jyz'
df.loc[df.name == "FIFA Manager 10", 'Code'] = '/m/05z_f50'
df.loc[df.name == "Kingdom Hearts 358/2 Days", 'Code'] = '/m/03c2kfr'
df.loc[df.name == "Fate/Unlimited Codes", 'Code'] = '/m/064qwbx'
df.loc[df.name == "Killing Floor", 'Code'] = '/m/05zl3dg'
df.loc[df.name == "Onslaught", 'Code'] = 'Onslaught'
df.loc[df.name == "Disney/Pixar Up", 'Code'] = 'Disney/Pixar Up'
df.loc[df.name == "Pokemon Rumble", 'Code'] = 'Pokemon Rumble'
df.loc[df.name == "Fortix", 'Code'] = 'Fortix'
df.loc[df.name == "Disney/Pixar Cars Race-O-Rama", 'Code'] = '/m/06zq8vm'
df.loc[df.name == "Disney/Pixar Toy Story Mania!", 'Code'] = '/m/05szv5k'
df.loc[df.name == "NBA Unrivaled", 'Code'] = 'NBA Unrivaled'
df.loc[df.name == "FIFA Soccer 09", 'Code'] = '/m/04czf4m'
df.loc[df.name == "FIFA Soccer 09 All-Play", 'Code'] = '/m/04czf4m'
df.loc[df.name == "Madden NFL 09", 'Code'] = '/m/02w6zqt'
df.loc[df.name == "Yakuza 2", 'Code'] = '/m/0gnlkv'
df.loc[df.name == "Assault Heroes 2", 'Code'] = '/m/03wcc37'
df.loc[df.name == "Omega Five", 'Code'] = 'Omega Five'
df.loc[df.name == "Guitar Hero: On Tour", 'Code'] = '/m/05szsdh'
df.loc[df.name == "Mario & Sonic at the Olympic Games", 'Code'] = '/m/02q8x4x'
df.loc[df.name == "Star Wars The Clone Wars: Jedi Alliance", 'Code'] = 'Star Wars The Clone Wars: Jedi Alliance'
df.loc[df.name == "Need for Speed Undercover", 'Code'] = '/m/047ph68'
df.loc[df.name == "AC/DC Live: Rock Band Track Pack", 'Code'] = '/g/121qyctc'
df.loc[df.name == "Sega Bass Fishing", 'Code'] = '/m/0dnlp8'
df.loc[df.name == "Warriors Orochi", 'Code'] = '/m/0282t9n'
df.loc[df.name == "Legendary", 'Code'] = 'Legendary'
df.loc[df.name == "Sega Bass Fishing", 'Code'] = '/m/0dnlp8'
df.loc[df.name == "The Witcher", 'Code'] = '/m/0gs0nr'
df.loc[df.name == "Hot Shots Tennis", 'Code'] = 'Hot Shots Tennis'
df.loc[df.name == "Disney/Pixar Cars Mater-National Championship", 'Code'] = '/m/02qjcgg'
df.loc[df.name == "Touch Detective 2 1/2", 'Code'] = '/m/02w0rh6'
df.loc[df.name == "Disney/Pixar Ratatouille", 'Code'] = '/m/02q532n'
df.loc[df.name == "Hot Shots Tennis", 'Code'] = 'Hot Shots Tennis'
df.loc[df.name == ".hack//GU Vol. 2//Reminisce", 'Code'] = '/m/0kymjcg'
df.loc[df.name == ".hack//G.U. vol. 3//Redemption", 'Code'] = '/m/07xgyjt'
df.loc[df.name == "Wii Play", 'Code'] = '/m/0h0604'
df.loc[df.name == "Fury", 'Code'] = 'Fury'
df.loc[df.name == "Monster Jam", 'Code'] = 'Monster Jam'
df.loc[df.name == "New Super Mario Bros.", 'Code'] = '/m/05_wxv'
df.loc[df.name == "Kingdom Hearts II", 'Code'] = '/m/05sp5n'
df.loc[df.name == "Call of Duty 3", 'Code'] = '/m/07z_fn'
df.loc[df.name == "OutRun 2006: Coast 2 Coast", 'Code'] = '/m/097pdv'
df.loc[df.name == "Race Driver 2006", 'Code'] = 'Race Driver 2006'
df.loc[df.name == "Need for Speed: Carbon", 'Code'] = '/m/0d1k7_'
df.loc[df.name == "Call of Duty 3", 'Code'] = '/m/07z_fn'
df.loc[df.name == "Need for Speed Carbon", 'Code'] = '/m/0d1k7_'
df.loc[df.name == "Naruto: Ultimate Ninja", 'Code'] = 'Naruto: Ultimate Ninja'
df.loc[df.name == "Disney/Pixar Cars", 'Code'] = '/m/0ck9j5'
df.loc[df.name == "Naruto: Clash of Ninja", 'Code'] = '/m/0792qj'
df.loc[df.name == "Astonishia Story", 'Code'] = '/m/0102m4pq'
df.loc[df.name == ".hack//G.U. vol. 1//Rebirth", 'Code'] = '/m/0kypyb4'
df.loc[df.name == "Night Watch", 'Code'] = 'Night Watch'
df.loc[df.name == "MotoGP", 'Code'] = '/m/09gd_q'
df.loc[df.name == "NASCAR", 'Code'] = '/m/0dtxz_'
df.loc[df.name == "Tokyo Xtreme Racer DRIFT", 'Code'] = '/m/027bpfk'
df.loc[df.name == "God of War", 'Code'] = '/m/05h8hz'
df.loc[df.name == "Game Tycoon", 'Code'] = 'Game Tycoon'
df.loc[df.name == "Battlefield 2", 'Code'] = '/m/03f_ln'
df.loc[df.name == "Guild Wars", 'Code'] = '/m/026br6k'
df.loc[df.name == "Mercenaries", 'Code'] = '/m/059z9v'
df.loc[df.name == "Need for Speed: Most Wanted (2005)", 'Code'] = '/m/08yjg0'
df.loc[9861, 'Code'] = '/m/08yjg0'
df.loc[df.name == "Super Monkey Ball Deluxe", 'Code'] = '/m/0dkdlp'
df.loc[df.name == "MLB", 'Code'] = '/m/0c13fb'
df.loc[df.name == "Star Wars: Battlefront II", 'Code'] = '/m/069jjt'
df.loc[df.name == "Lego Star Wars", 'Code'] = 'Lego Star Wars'
df.loc[df.name == "LEGO Star Wars", 'Code'] = 'Lego Star Wars'
df.loc[df.name == "The King of Fighters 02/03", 'Code'] = 'The King of Fighters 02/03'
df.loc[df.name == "In the Groove", 'Code'] = '/m/03qt3h'
df.loc[df.name == "Dr. Mario / Puzzle League", 'Code'] = '/m/09x3fj'
df.loc[df.name == "Dragon Ball Z: Budokai Tenkaichi", 'Code'] = 'Dragon Ball Z: Budokai Tenkaichi'
df.loc[df.name == "Romance of the Three Kingdoms X", 'Code'] = '/m/06_14j'
df.loc[df.name == "DK: King of Swing", 'Code'] = '/m/06gg3z'
df.loc[df.name == "Cold War", 'Code'] = 'Cold War'
df.loc[df.name == "Chaos Field", 'Code'] = '/m/0dsttc'
df.loc[df.name == "Shining Tears", 'Code'] = '/m/08y2lx'
df.loc[df.name == "Dead to Rights: Reckoning", 'Code'] = '/m/02x3z76'
df.loc[df.name == "Death by Degrees", 'Code'] = '/m/073jy7'
df.loc[df.name == "World of Warcraft", 'Code'] = '/m/021dvx'
df.loc[df.name == "Rome: Total War", 'Code'] = '/m/02_wm5'
df.loc[df.name == "Ninja Gaiden", 'Code'] = '/m/0fd2rd'
df.loc[df.name == "Pikmin 2", 'Code'] = '/m/02xn2f'
df.loc[df.name == "Viewtiful Joe", 'Code'] = '/m/03nxpv'
df.loc[df.name == "Call of Duty: United Offensive", 'Code'] = '/m/031_9z'
df.loc[df.name == "Tales of Symphonia", 'Code'] = '/m/03kd6v'
df.loc[df.name == "Warhammer 40,000: Dawn of War", 'Code'] = '/m/03q8_3'
df.loc[df.name == "Metal Gear Solid: The Twin Snakes", 'Code'] = '/m/02wlm1'
df.loc[df.name == "Classic NES Series: The Legend of Zelda", 'Code'] = '/m/01633s'
df.loc[df.name == "NBA Ballers", 'Code'] = '/m/09yrt1'
df.loc[df.name == "Shin Megami Tensei: Nocturne", 'Code'] = '/m/05pgsp'
df.loc[df.name == "Phantom Brave", 'Code'] = '/m/047b8h'
df.loc[df.name == "RollerCoaster Tycoon 3", 'Code'] = '/m/044yrn'
df.loc[df.name == "Mario vs. Donkey Kong", 'Code'] = '/m/040gqk'
df.loc[df.name == "TOCA Race Driver 2: The Ultimate Racing Simulator", 'Code'] = '/m/05b6nch'
df.loc[df.name == "Mario Power Tennis", 'Code'] = '/m/046tc0'
df.loc[df.name == "Syberia II", 'Code'] = '/m/050ff2'
df.loc[df.name == "Final Fantasy Crystal Chronicles", 'Code'] = '/m/0262yb'
df.loc[df.name == "Tony Hawk's Underground 2", 'Code'] = 'Tony Hawk\'s Underground 2'
df.loc[df.name == "NCAA Football 2005", 'Code'] = 'NCAA Football 2005'
df.loc[df.name == "Star Wars: Battlefront", 'Code'] = '/m/044ccj'
df.loc[df.name == "FIFA Soccer 2005", 'Code'] = 'FIFA Soccer 2005'
df.loc[df.name == "R-Type Final", 'Code'] = '/m/06q6yp'
df.loc[df.name == "Dance Dance Revolution Extreme", 'Code'] = '/m/04ssjh'
df.loc[df.name == "Evil Genius", 'Code'] = '/m/03xbk0'
df.loc[df.name == "Feel the Magic: XY/XX", 'Code'] = '/m/044_v_'
df.loc[df.name == "TrackMania (2003)s", 'Code'] = 'TrackMania'
df.loc[df.name == "Crusader Kings", 'Code'] = '/m/079rt6'
df.loc[df.name == "Samurai Warriors: Xtreme Legends", 'Code'] = 'Samurai Warriors: Xtreme Legends'
df.loc[df.name == "Sega Superstars", 'Code'] = '/m/0459_r'
df.loc[df.name == "Dynasty Warriors 4: Empires", 'Code'] = 'Dynasty Warriors 4: Empires'
df.loc[df.name == ".hack//Quarantine Part 4", 'Code'] = '/m/07k7c5'
df.loc[df.name == "Grand Theft Auto", 'Code'] = '/m/0c40ym'
df.loc[df.name == "Monster Hunter", 'Code'] = '/m/04zshp'
df.loc[df.name == "True Crime: Streets of LA", 'Code'] = 'True Crime: Streets of LA'
df.loc[df.name == "Excitebike", 'Code'] = '/m/02sdnc'
df.loc[df.name == "The Incredibles", 'Code'] = 'The Incredibles'
df.loc[df.name == "Lifeline", 'Code'] = 'Lifeline'
df.loc[df.name == "Spyro Orange: The Cortex Conspiracy", 'Code'] = 'Spyro Orange: The Cortex Conspiracy'
df.loc[df.name == "Rapala Pro Fishing", 'Code'] = '/m/0kz1jrh'
df.loc[df.name == "Classic NES Series: Metroid", 'Code'] = '/m/04d5rb'
df.loc[df.name == "Disney/Pixar The Incredibles", 'Code'] = 'The Incredibles'
df.loc[df.name == "Two Thrones", 'Code'] = '/m/02wvl8c'
df.loc[df.name == "Under the Skin", 'Code'] = 'Under the Skin'
df.loc[df.name == "ChoroQ", 'Code'] = 'ChoroQ'
df = df.drop_duplicates(subset=['Code'], keep='last')